Jobs Data Engineer

Data Engineer — Remote (GMT +1-5)

📍 Remote | 🕐 One interview. That's it.

WHO WE ARE

SouthRivers Data, we're an engineering-led company - built by engineers, run by engineers. That means no explaining why tech debt matters, no translating "we need refactoring time" into business speak, and no decisions made by people who've never written a line of code. We get it, because we've been there.

We believe that a great engineer is defined by two things equally: technical mastery and the ability to work with people. One without the other isn't enough for us - and probably isn't enough for you either.

THE ROLE

We're looking for a Data Engineer to join our project and work on data-intensive client projects - think DWH modernization, data lakehouse architecture, and pipeline engineering

You'll be engaged on a project basis, with clear scope and a team that actually understands your work.

WHAT WE EXPECT

Required:

• Strong Python and SQL - you write clean, production-grade code
• Apache Spark - you know how it works under the hood, not just the API
• Workflow orchestration with Airflow, Dagster, or equivalent
• Hands-on experience with at least one major cloud: AWS / Azure / GCP
• Solid understanding of Data Engineering principles, Data Modelling, dimensional design, and best practices
• Experience with DWH and Lakehouse architectures — you've designed or maintained one, not just heard the terms

Nice to Have:

• dbt
• CI/CD experience in a data context (GitHub Actions, etc.)

THE PROCESS

One 1-hour interview with us. Possibly one short call with the client. That's the entire process - we respect your time and we've structured things so we can make a decision fast.

No take-home assignments.

THE SETUP

• Fully remote - work from wherever you are
• Contract / B2B engagement
• 2–4 week onboarding notice window

If you've been burned by companies that talk about engineering culture but are run by spreadsheets - this is the alternative.

Apply or reach out directly. We read every message.

Our client is a fast-growing, fast-paced company on a mission to build a modern data platform that enables smarter decision-making across the business. They are focused on creating a single, trusted view of performance across marketing, product, and operations. Leveraging a modern cloud data stack, they empower teams with reliable, accessible, and actionable data.

Their teams are made up of driven professionals who enjoy solving complex data challenges, collaborating closely across functions, and building scalable analytics solutions. They value individuals who are proactive, detail-oriented, and passionate about data, and who thrive in collaborative and fast-paced environments.
 

About the Role:

We are seeking a Data Engineer for our client. In this role, you will take ownership of building and maintaining a modern data platform, ensuring reliable data flows and enabling analytics across the organization. You will work closely with a BI Analyst to deliver a clean, well-structured data layer that supports reporting and self-service analytics.

This is the first technical hire in a growing data team, offering a unique opportunity to shape the platform, define best practices, and influence how data is used across the company.
 

Responsibilities:

• Build, maintain, and own the modern data platform;
• Develop and manage robust, scalable data ingestion pipelines;
• Design and maintain well-structured data models using dbt;
• Ensure the data warehouse is clean, reliable, and analytics-ready;
• Collaborate closely with the BI Analyst to support reporting and analytics needs;
• Implement data governance practices, including documentation, testing, and data quality checks;
• Evaluate and introduce AI tools to improve development efficiency and platform monitoring.
   

Requirements:

• 6+ years of experience building and maintaining modern cloud data warehouses;
• 3+ years of hands-on experience with Google BigQuery;
• Strong experience with Fivetran, dbt Cloud, or similar tools;
• Proven experience designing analytics-ready data models for BI tools;
• Experience working with modern data stacks and ELT pipelines;
• Familiarity with data governance, testing, and quality assurance practices;
• Hands-on experience using AI-assisted tools within engineering workflows;
• Strong problem-solving skills and attention to detail;
• Ability to work independently and collaborate with cross-functional teams;
• Good communication skills and a proactive mindset.
   

We Offer:

• Competitive market salary;
• Fully remote work;
• Convenient and somewhat flexible working hours;
• 28 days of paid time off per calendar year;
• The chance to work on meaningful, socially valuable products alongside a highly professional, international team;
• .Interesting technical challenges with opportunities to grow and learn

We are looking for an experienced Senior Site Reliability Engineer to ensure the stability and reliability of a platform operating in a hybrid environment (Azure + on-premise).

This role combines SRE, DevOps, and backend engineering mindset, with a strong focus on production systems and direct customer-facing troubleshooting.

Responsibilities

• Manage deployments across Azure and on-premise infrastructure
• Maintain and improve production systems at scale to ensure availability and performance
• Participate in live troubleshooting sessions with customers
• Handle incidents: analysis, resolution, and postmortems
• Build and improve CI/CD pipelines and automation workflows
• Work with containers (Docker, Kubernetes)
• Collaborate with engineering teams to deliver infrastructure improvements
• Document processes and maintain runbooks

Requirements

• 5+ years of experience in SRE / DevOps / Infrastructure roles
• Strong hands-on experience with Kubernetes (must-have)
• Experience operating production systems at scale
• Experience with Azure (required)
• Solid knowledge of Docker and containerization
• Experience with CI/CD pipelines and automation
• Strong C# programming skills and understanding of software architecture
• Experience with customer-facing troubleshooting
• Strong communication skills and ability to work remotely

Nice to Have

• Experience with AWS (in addition to Azure)
• PowerShell scripting
• Infrastructure as Code (IaC) experience
• Experience with multiple CI/CD or pipeline tools

What We Offer

• Remote work environment
• Full-time or B2B contract options
• Opportunity to work on a mission-critical product
• Direct impact on system stability and customer experience

• Competitive compensation                                                                   

  Additional Information

• Project start: end of April (April 29)
• Full-time engagement
• Long-term project (1+ year)
• Fully remote work setup
• Company provides all necessary equipment

Description

The client is transforming its global data infrastructure to deliver faster, more scalable, and more intelligent analytics capabilities. As part of this journey, we’re hiring a Data Engineering to manage the technical delivery and operational resilience of our core data platform.

This role sits at the intersection of engineering leadership, platform reliability, and architecture – helping us ensure that data flows are healthy, scalable, and ready for production. You’ll work across project delivery, production support, and platform enhancement initiatives while mentoring a growing team of engineers.

Requirements

Familiarity with Google Cloud Platform, including BigQuery, Cloud Composer (Airflow), Compute Engine, and Monitoring.
Middle level in Python, including experience in building, testing, and deploying robust ETL/ELT pipelines in production
Experience developing data quality frameworks, including automated tests, cross-dataset validations, and anomaly detection across diverse data assets
Advanced SQL skills, including data modeling (star/snowflake/3NF), optimization, and writing performant queries tailored to BigQuery’s slot-based execution model
Solid working knowledge of DBT, including incremental models, testing, documentation, and advanced features like custom macros
Demonstrated ability to optimize BigQuery workloads through partitioning, clustering, materialized views, and cost-aware development practices
Experience working with ETL orchestration tools, ideally Cloud Composer or similar frameworks (Kestra, Dagster, etc.).
Hands-on experience consuming and managing APIs for data extraction.
Exposure to Site Reliability Engineering (SRE) best practices, including ticket triage, incident management, and documenting runbooks/SOPs
Familiar with Git and modern software development workflows, including pull requests and code reviews
Comfortable working in an agile team environment, with the ability to multitask and reprioritize based on changing project needs
Clear and effective communication skills, with the ability to engage technical and non-technical stakeholders alike

Job responsibilities

Designing, building, and maintaining scalable, reliable data pipelines using Python,SQL, DBT, and Google Cloud Platform (GCP) services like BigQuery and Cloud Composer.
Contributing to the development and evolution of our data quality framework, ensuring robust automated testing and cross-dataset validation across all critical data assets
Writing and optimizing advanced SQL to power data models, analytics, and reporting pipelines, with a focus on performance and efficiency within BigQuery
Developing and maintaining DBT models, including testing, documentation, incremental loading strategies, and the creation of reusable macros
Supporting day-to-day incident and ticket resolution, including root cause analysis and documentation of runbooks/SOPs to drive platform reliability
Working with APIs and external data sources to extract, normalize, and integrate new datasets into the platform
Participating in agile ceremonies (stand-ups, retros, planning), contributing to sprint goals and helping support the wider team objectives
Actively contributing to code reviews, documentation, and peer learning – helping to raise engineering standards and share knowledge within the team
Monitoring system health and pipeline performance using GCP-native tools and dashboards, and proactively identifying opportunities for cost or performance optimization

Bonus points for

GCP Data Engineer certification
Prior experience in media, marketing, or digital advertising analytics
Experience implementing data quality frameworks and governance tools
Familiarity with cost optimization strategies for BigQuery and other GCP services

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.

Project overview

The Exposure Platform is a long running enterprise data transformation initiative focused on replacing legacy SQL based logic with modern, scalable data processing solutions. The platform handles large data volumes and supports multiple business domains through a shared and business critical codebase. The work emphasises maintainability, performance, and strong software engineering practices across the organisation.

Team

You will work in a small cross functional data engineering team consisting of senior data engineers and software engineers. The team collaborates closely through code reviews, shared design discussions, and agreed engineering standards while contributing to a common codebase. The team is currently expanding and values structured collaboration and technical ownership.

Position overview

We are looking for a Senior Data Engineer to support a large scale transformation from SQL Server based systems to a Databricks and Delta Lake platform. You will focus on enterprise grade data engineering and software development, building maintainable and scalable data processing solutions used by multiple teams. This role is not focused on analytics or reporting, but on core data transformation and platform development.

Technology stack

Databricks, Delta Lake, Python, PySpark, SQL Server, Azure Data Factory, Azure DevOps, Git, CI CD pipelines

Responsibilities

• Read, understand, and reason about complex SQL stored procedures and embedded business logic
• Redesign and implement existing SQL logic as clean and maintainable Python and PySpark code in Databricks
• Develop production grade transformation code using reusable packages, modules, and components
• Apply software engineering best practices including clean code, object oriented design, modularisation, and refactoring
• Design and evolve data models across Bronze, Silver, and Gold layers
• Work with very large data volumes and highly parallel event driven data transformations
• Participate actively in code reviews and technical design discussions
• Contribute to the stability, scalability, and long term maintainability of the shared data engineering codebase

Requirements

• Strong experience with Python and PySpark in production data engineering environments
• Hands on experience working with Databricks and Delta Lake
• Strong SQL skills with the ability to read, analyse, and translate complex stored procedures
• Experience working in large shared codebases beyond notebook based development
• Solid understanding of object oriented programming and software engineering principles
• Experience applying clean code practices, refactoring, and maintainable design
• Strong background in data modelling, including transactional and analytical models
• Experience working with layered data architectures such as Bronze, Silver, and Gold
• Ability to analyse existing code line by line and explain technical and business logic clearly

Nice to have

• Experience with Power BI for data consumption or validation
• Exposure to enterprise scale data platforms in complex organisational environments

• Join the Data Engineering team to contribute to the ongoing maintenance and improvement of an internal LLM-powered assistant that uses hosted LLM APIs and internal knowledge sources, with a focus on reliability, retrieval quality, and operational excellence.

• Responsibilities:

  • Maintain and enhance ingestion/enrichment pipelines for internal content (parsing/extraction, normalization, metadata enrichment, deduplication, and quality monitoring)
  • Improve indexing and retrieval performance and quality (chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching) and support hybrid retrieval capabilities (vector + keyword/BM25 + metadata)
  • Implement and maintain access-aware retrieval by propagating/enforcing document permissions through indexing and query-time filters, including audit logs and validation tests
  • Improve source attribution so responses reliably point to the correct documents and sections in a consistent format.
  • Extend and harden tool/workflow execution and automations (scheduled/trigger-based), including retries, timeouts, idempotency, concurrency controls, and run history
  • Develop and maintain evaluation and regression testing (golden sets, automated scoring) and support structured comparisons across LLM providers/models as required
  • Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

• Mandatory Skills Description:

  8+ years of hands-on experience in Data Science and 5+ years in Machine Learning, with a proven track record, demonstrated through a robust portfolio of projects.
  Strong programming skills in languages such as Python and familiarity building ETL pipelines.
  Expertise in SQL and experience with both relational (preferably Postgres) and NoSQL databases (Open Search or Elastic Search)
  Familiarity with cloud platforms (e.g., AWS) and their services.
  Experience with version control systems (e.g., Git) and CI/CD pipelines.
  Ability to build scalable infrastructure to embed and search very large number of documents.
  Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines.
  Expertise in ML inference optimizations
  Solid experience with Hybrid RAG, chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching, etc.
  Knowledge of network optimization for distributed ML training and inference.
  Understanding of distributed training patterns and checkpointing strategies.
  Strong English skills (B2 and higher)
  Strong verbal and written communication skills.
  Ability to work independently and collaborate in a group.

• Nice-to-Have Skills Description:

  Agile certification
  AWS/Oracle/Microsoft attestations and certifications
  Domain knowledge - Trading and Capital Markets

• Languages:
  • English: C1 Advanced

We are seeking a highly skilled Snowflake Data Engineer with 7 years of IT experience to design, build, and optimize scalable data pipelines and cloud-based solutions across AWS, Azure, and GCP. The ideal candidate will have strong expertise in Snowflake, ETL Tools like DBT, Python, visualization tools like Tableau and modern CI/CD practices, with a deep understanding of data governance, security, and role-based access control (RBAC). Knowledge of data modeling methodologies (OLTP, OLAP, Data Vault 2.0), data quality frameworks, Stream lit application development and SAP integration and infrastructure-as-code with Terraform is essential. Experience working with different file formats such as JSON, Parquet, CSV, and XML is highly valued.

• Responsibilities:

  • Design and develop data pipelines using Snowflake and Snow pipe for real-time and batch ingestion.
  • Implement CI/CD pipelines in Azure DevOps for seamless deployment of data solutions.
  • Automate DBT jobs to streamline transformations and ensure reliable data workflows.
  • Apply data modeling techniques including OLTP, OLAP, and Data Vault 2.0 methodologies to design scalable architectures.
  • Document data models, processes, and workflows clearly for future reference and knowledge sharing.
  • Build data tests, unit tests, and mock data frameworks to validate and maintain reliability of data solutions.
  • Develop Streamlit applications integrated with Snowflake to deliver interactive dashboards and self-service analytics.
  • Integrate SAP data sources into Snowflake pipelines for enterprise reporting and analytics.
  • Leverage SQL expertise for complex queries, transformations, and performance optimization.
  • Integrate cloud services across AWS, Azure, and GCP to support multi-cloud data strategies.
  • Develop Python scripts for ETL/ELT processes, automation, and data quality checks.
  • Implement infrastructure-as-code solutions using Terraform for scalable and automated cloud deployments.
  • Manage RBAC and enforce data governance policies to ensure compliance and secure data access.
  • Collaborate with cross-functional teams including business analysts, and business stakeholders to deliver reliable data solutions.

• Mandatory Skills Description:

  • Strong proficiency in Snowflake (Snowpipe, RBAC, performance tuning).
  • Hands-on experience with Python , SQL , Jinja , JavaScript for data engineering tasks.
  • CI/CD expertise using Azure DevOps (build, release, version control).
  • Experience automating DBT jobs for data transformations.
  • Experience building Streamlit applications with Snowflake integration.
  • Cloud services knowledge across AWS (S3, Lambda, Glue), Azure (Data Factory, Synapse), and GCP (BigQuery, Pub/Sub).

The product we are working on is one of TOP-3 navigation systems, complex web services, and other solutions related to it. The web and mobile apps handle information at a massive scale and extend well beyond the search, giving people and companies a lot of new, useful options.

This role focuses on executing critical migration projects within the backend infrastructure of the project. The Backend Infrastructure team is undertaking several large-scale migrations to modernize its systems, improve reliability, and reduce maintenance overhead. This TVC position will be instrumental in performing the hands-on work required for these migrations, working closely with the infrastructure team and other Backend teams.
 

Responsibilities:
 

• Execute Migrations: Actively participate in and drive the execution of large-scale code and system migrations across various backend services. Some examples include:
  • migrating event processing systems from custom infrastructure to managed infrastructure solutions;
  • Transitioning services from custom OpenCensus metrics collection to OpenTelemetry;
  • migrating custom metrics to standard OpenTelemetry metrics.
• Code Modification and Updates: Update and refactor existing codebases (primarily Java) to align with new libraries, platforms, and infrastructure.
• Testing: Work with the Infrastructure team to create a testing plan for migrations to ensure that changes do not break running services and execute the test plans.
• Collaboration: Work closely with the Backend Infrastructure team and other software engineers to understand migration requirements, plan execution strategies, and ensure smooth transitions with minimal disruption.
• Problem Solving: Investigate, debug, and resolve technical issues and complexities encountered during the migration processes.
• Documentation: Maintain clear and concise documentation for migration plans, processes, changes made, and outcomes.

• Best Practices: Adhere to software development best practices, ensuring code quality, and follow established guidelines for infrastructure changes.

   

Requirements:

• 5+ years of hands-on experience in backend software development.
• Strong proficiency in Java programming.
• Strong communication and interpersonal skills, with the ability to collaborate effectively within a technical team environment.
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
• Good spoken and written English level — Upper-Intermediate or higher.
   

Nice to have:

• Experience with observability frameworks such as OpenTelemetry or OpenCensus.
• Familiarity with gRPC.
• Knowledge of Google Cloud Platform (GCP) services, particularly data processing services like Dataflow.
   

We offer:

• Opportunities to develop in various areas;
• Compensation package (20 paid vacation days, paid sick leaves);
• Flexible working hours;
• Medical insurance;
• English courses with a native speaker, yoga (Zoom);
• Paid tech training and other activities for professional growth;
• Hybrid work mode (∼3 days in the office);
• International business trips

• Comfortable office.

   

If your qualifications and experience match the requirements of the position, our recruitment team will reach out to you in a week maximum. Please rest assured that we carefully consider each candidate, but due to the amount of applications, the review and further processing of your candidacy may take some time.

Join the Data Engineering team to contribute to the ongoing maintenance and improvement of an internal LLM-powered assistant that uses hosted LLM APIs and internal knowledge sources, with a focus on reliability, retrieval quality, and operational excellence.

• Responsibilities:

  • Maintain and enhance ingestion/enrichment pipelines for internal content (parsing/extraction, normalization, metadata enrichment, deduplication, and quality monitoring)
  • Improve indexing and retrieval performance and quality (chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching) and support hybrid retrieval capabilities (vector + keyword/BM25 + metadata)
  • Implement and maintain access-aware retrieval by propagating/enforcing document permissions through indexing and query-time filters, including audit logs and validation tests
  • Improve source attribution so responses reliably point to the correct documents and sections in a consistent format.
  • Extend and harden tool/workflow execution and automations (scheduled/trigger-based), including retries, timeouts, idempotency, concurrency controls, and run history
  • Develop and maintain evaluation and regression testing (golden sets, automated scoring) and support structured comparisons across LLM providers/models as required
  • Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

• Mandatory Skills Description:

  8+ years of hands-on experience in Data Science and 5+ years in Machine Learning, with a proven track record, demonstrated through a robust portfolio of projects.
  Strong programming skills in languages such as Python and familiarity building ETL pipelines.
  Expertise in SQL and experience with both relational (preferably Postgres) and NoSQL databases (Open Search or Elastic Search)
  Familiarity with cloud platforms (e.g., AWS) and their services.
  Experience with version control systems (e.g., Git) and CI/CD pipelines.
  Ability to build scalable infrastructure to embed and search very large number of documents.
  Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines.
  Expertise in ML inference optimizations
  Solid experience with Hybrid RAG, chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching, etc.
  Knowledge of network optimization for distributed ML training and inference.
  Understanding of distributed training patterns and checkpointing strategies.
  Strong English skills (B2 and higher)
  Strong verbal and written communication skills.
  Ability to work independently and collaborate in a group.

• Project Description:

  We are seeking a highly skilled Snowflake Data Engineer with 7 years of IT experience to design, build, and optimize scalable data pipelines and cloud-based solutions across AWS, Azure, and GCP. The ideal candidate will have strong expertise in Snowflake, ETL Tools like DBT, Python, visualization tools like Tableau and modern CI/CD practices, with a deep understanding of data governance, security, and role-based access control (RBAC). Knowledge of data modeling methodologies (OLTP, OLAP, Data Vault 2.0), data quality frameworks, Stream lit application development and SAP integration and infrastructure-as-code with Terraform is essential. Experience working with different file formats such as JSON, Parquet, CSV, and XML is highly valued.

• Responsibilities:

  • Design and develop data pipelines using Snowflake and Snow pipe for real-time and batch ingestion.
  • Implement CI/CD pipelines in Azure DevOps for seamless deployment of data solutions.
  • Automate DBT jobs to streamline transformations and ensure reliable data workflows.
  • Apply data modeling techniques including OLTP, OLAP, and Data Vault 2.0 methodologies to design scalable architectures.
  • Document data models, processes, and workflows clearly for future reference and knowledge sharing.
  • Build data tests, unit tests, and mock data frameworks to validate and maintain reliability of data solutions.
  • Develop Streamlit applications integrated with Snowflake to deliver interactive dashboards and self-service analytics.
  • Integrate SAP data sources into Snowflake pipelines for enterprise reporting and analytics.
  • Leverage SQL expertise for complex queries, transformations, and performance optimization.
  • Integrate cloud services across AWS, Azure, and GCP to support multi-cloud data strategies.
  • Develop Python scripts for ETL/ELT processes, automation, and data quality checks.
  • Implement infrastructure-as-code solutions using Terraform for scalable and automated cloud deployments.
  • Manage RBAC and enforce data governance policies to ensure compliance and secure data access.
  • Collaborate with cross-functional teams including business analysts, and business stakeholders to deliver reliable data solutions.

• Mandatory Skills Description:

  • Strong proficiency in Snowflake (Snowpipe, RBAC, performance tuning).
  • Hands-on experience with Python , SQL , Jinja , JavaScript for data engineering tasks.
  • CI/CD expertise using Azure DevOps (build, release, version control).
  • Experience automating DBT jobs for data transformations.
  • Experience building Streamlit applications with Snowflake integration.
  • Cloud services knowledge across AWS (S3, Lambda, Glue), Azure (Data Factory, Synapse), and GCP (BigQuery, Pub/Sub).

• Nice-to-Have Skills Description:

  - Cloud certifications is a plus

• Languages:
  • English: B2 Upper Intermediate

Project Description:

We are seeking a highly skilled Snowflake Data Engineer with 7 years of IT experience to design, build, and optimize scalable data pipelines and cloud-based solutions across AWS, Azure, and GCP. The ideal candidate will have strong expertise in Snowflake, ETL Tools like DBT, Python, visualization tools like Tableau and modern CI/CD practices, with a deep understanding of data governance, security, and role-based access control (RBAC). Knowledge of data modeling methodologies (OLTP, OLAP, Data Vault 2.0), data quality frameworks, Stream lit application development and SAP integration and infrastructure-as-code with Terraform is essential. Experience working with different file formats such as JSON, Parquet, CSV, and XML is highly valued.

Responsibilities:

• Design and develop data pipelines using Snowflake and Snow pipe for real-time and batch ingestion.
• Implement CI/CD pipelines in Azure DevOps for seamless deployment of data solutions.
• Automate DBT jobs to streamline transformations and ensure reliable data workflows.
• Apply data modeling techniques including OLTP, OLAP, and Data Vault 2.0 methodologies to design scalable architectures.
• Document data models, processes, and workflows clearly for future reference and knowledge sharing.
• Build data tests, unit tests, and mock data frameworks to validate and maintain reliability of data solutions.
• Develop Streamlit applications integrated with Snowflake to deliver interactive dashboards and self-service analytics.
• Integrate SAP data sources into Snowflake pipelines for enterprise reporting and analytics.
• Leverage SQL expertise for complex queries, transformations, and performance optimization.
• Integrate cloud services across AWS, Azure, and GCP to support multi-cloud data strategies.
• Develop Python scripts for ETL/ELT processes, automation, and data quality checks.
• Implement infrastructure-as-code solutions using Terraform for scalable and automated cloud deployments.
• Manage RBAC and enforce data governance policies to ensure compliance and secure data access.
• Collaborate with cross-functional teams including business analysts, and business stakeholders to deliver reliable data solutions.

Mandatory Skills Description:

• Strong proficiency in Snowflake (Snowpipe, RBAC, performance tuning).
• Hands-on experience with Python , SQL , Jinja , JavaScript for data engineering tasks.
• CI/CD expertise using Azure DevOps (build, release, version control).
• Experience automating DBT jobs for data transformations.
• Experience building Streamlit applications with Snowflake integration.
• Cloud services knowledge across AWS (S3, Lambda, Glue), Azure (Data Factory, Synapse), and GCP (BigQuery, Pub/Sub).

Nice-to-Have Skills Description:

- Cloud certifications is a plus

Languages:

English: B2 Upper Intermediate

Are you passionate about building large-scale cloud data infrastructure that makes a real difference? We are looking for a Senior Data Engineer to join our team and work on an impactful healthcare technology project. This role offers a remote work format with the flexibility to collaborate across international teams.

At Sigma Software, we deliver innovative IT solutions to global clients in multiple industries, and we take pride in projects that improve lives. Joining us means working with cutting-edge technologies, contributing to meaningful initiatives, and growing in a supportive environment.

CUSTOMER
Our client is a leading medical technology company. Its portfolio of products, services, and solutions is at the center of clinical decision-making and treatment pathways. Patient-centered innovation has always been, and will always be, at the core of the company. The client is committed to improving patient outcomes and experiences, regardless of where patients live or what they face. The Customer is innovating sustainably to provide healthcare for everyone, everywhere. 

PROJECT
The project focuses on building and maintaining large-scale cloud-based data infrastructure for healthcare applications. It involves designing efficient data pipelines, creating self-service tools, and implementing microservices to simplify complex processes. The work will directly impact how healthcare providers access, process, and analyze critical medical data, ultimately improving patient care.

Responsibilities:

• Collaborate with the Product Owner and team leads to define and design efficient pipelines and data schemas
• Build and maintain infrastructure using Terraform for cloud platforms
• Design and implement large-scale cloud data infrastructure, self-service tooling, and microservices
• Work with large datasets to optimize performance and ensure seamless data integration
• Develop and maintain squad-specific data architectures and pipelines following ETL and Data Lake principles
• Discover, analyze, and organize disparate data sources into clean, understandable schemas

Requirements:

• Hands-on experience with cloud computing services in data and analytics
• Experience with data modeling, reporting tools, data governance, and data warehousing
• Proficiency in Python and PySpark for distributed data processing
• Experience with Azure, Snowflake, and Databricks
• Experience with Docker and Kubernetes
• Knowledge of infrastructure as code (Terraform)
• Advanced SQL skills and familiarity with big data databases such as Snowflake, Redshift, etc.
• Experience with stream processing technologies such as Kafka, Spark Structured Streaming
• At least an Upper-Intermediate level of English 

Are you passionate about building large-scale cloud data infrastructure that makes a real difference? We are looking for a Senior Data Engineer to join our team and work on an impactful healthcare technology project. This role offers a remote work format with the flexibility to collaborate across international teams.

At Sigma Software, we deliver innovative IT solutions to global clients in multiple industries, and we take pride in projects that improve lives. Joining us means working with cutting-edge technologies, contributing to meaningful initiatives, and growing in a supportive environment.

CUSTOMER
Our client is a leading medical technology company. Its portfolio of products, services, and solutions is at the center of clinical decision-making and treatment pathways. Patient-centered innovation has always been, and will always be, at the core of the company. The client is committed to improving patient outcomes and experiences, regardless of where patients live or what they face. The Customer is innovating sustainably to provide healthcare for everyone, everywhere. 

PROJECT
The project focuses on building and maintaining large-scale cloud-based data infrastructure for healthcare applications. It involves designing efficient data pipelines, creating self-service tools, and implementing microservices to simplify complex processes. The work will directly impact how healthcare providers access, process, and analyze critical medical data, ultimately improving patient care.

Responsibilities:

• Collaborate with the Product Owner and team leads to define and design efficient pipelines and data schemas
• Build and maintain infrastructure using Terraform for cloud platforms
• Design and implement large-scale cloud data infrastructure, self-service tooling, and microservices
• Work with large datasets to optimize performance and ensure seamless data integration
• Develop and maintain squad-specific data architectures and pipelines following ETL and Data Lake principles
• Discover, analyze, and organize disparate data sources into clean, understandable schemas

Requirements:

• Possibility to meet clients annually in Europe
• Hands-on experience with cloud computing services in data and analytics
• Experience with data modeling, reporting tools, data governance, and data warehousing
• Proficiency in Python and PySpark for distributed data processing
• Experience with Azure, Snowflake, and Databricks
• Experience with Docker and Kubernetes
• Knowledge of infrastructure as code (Terraform)
• Advanced SQL skills and familiarity with big data databases such as Snowflake, Redshift, etc.
• Experience with stream processing technologies such as Kafka, Spark Structured Streaming
• At least an Upper-Intermediate level of English 

Чи захоплюєтесь ви створенням масштабної хмарної інфраструктури даних, яка має реальний вплив? Ми шукаємо Senior Data Engineer, який приєднається до нашої команди та працюватиме над важливим проєктом у сфері медичних технологій. Ця роль передбачає віддалений формат роботи з можливістю співпрацювати з міжнародними командами.

У Sigma Software ми створюємо інноваційні ІТ-рішення для глобальних клієнтів у різних галузях і пишаємося проєктами, які покращують життя людей. Приєднавшись до нас, ви працюватимете з передовими технологіями, робитимете внесок у значущі ініціативи та розвиватиметеся в підтримуючому середовищі.

Клієнт:
Наш клієнт — провідна компанія у сфері медичних технологій. Її портфель продуктів, сервісів та рішень знаходиться в центрі процесів клінічного прийняття рішень і побудови шляхів лікування. Інновації, орієнтовані на пацієнтів, завжди були і залишаються основою діяльності компанії. Клієнт прагне покращувати результати лікування та досвід пацієнтів незалежно від того, де вони живуть і з якими викликами стикаються. Компанія інноваційно розвивається, щоб забезпечити доступ до медицини для кожного, всюди.

Проєкт:
Проєкт зосереджений на створенні та підтримці масштабної хмарної інфраструктури даних для медичних застосунків. Він включає проєктування ефективних data pipelines, створення self-service інструментів та реалізацію мікросервісів для спрощення складних процесів. Робота безпосередньо впливатиме на те, як медичні установи отримують доступ до критично важливих медичних даних, обробляють їх та аналізують, що зрештою покращує якість медичної допомоги пацієнтам.

 

Обов'язки: 

• Співпрацювати з Product Owner та технічними лідами для визначення та проєктування ефективних pipelines і схем даних
• Будувати та підтримувати інфраструктуру для хмарних платформ за допомогою Terraform
• Проєктувати та впроваджувати масштабну хмарну інфраструктуру даних, self-service інструменти та мікросервіси
• Працювати з великими наборами даних для оптимізації продуктивності та забезпечення безперебійної інтеграції даних
• Розробляти та підтримувати архітектури даних і pipelines для команди відповідно до принципів ETL та Data Lake
• Виявляти, аналізувати та впорядковувати різнорідні джерела даних у зрозумілі та чисті схеми

Вимоги:

• Можливість раз на рік зустрічатися з клієнтами в Європі
• Практичний досвід роботи з хмарними сервісами для даних та аналітики
• Досвід data modeling, reporting tools, data governance та data warehousing
• Впевнене володіння Python і PySpark для розподіленої обробки даних
• Досвід роботи з Azure, Snowflake та Databricks
• Досвід роботи з Docker та Kubernetes
• Знання infrastructure as code (Terraform)
• Просунуті навички SQL та знайомство з big data базами даних, такими як Snowflake, Redshift тощо
• Досвід роботи зі stream processing технологіями, такими як Kafka, Spark Structured Streaming
• Рівень англійської не нижче Upper-Intermediate

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

PwC Poland’s Cloud & Digital team supports global cloud projects across Cloud Strategy, Migrations, Data Analytics, and DevOps. We help clients adopt cloud infrastructure, modernize data platforms, and optimize operations. This hybrid role is based in Warsaw with flexible working options.

Your future role:

• Building data platforms (data warehouses, lakes, lakehouses) using Azure Databricks, MS Fabric, Azure Data Factory.
• Designing data flows using medallion architecture and supporting data migrations from legacy systems.
• Conducting data assessments with Data Modelers/Analysts and addressing data quality issues.
• Working with senior stakeholders to gather requirements and support modern data architecture design.
• Supporting Data Governance activities, especially around MDM and Data Quality.
• Understanding Data Science/Analytics use cases in industries like Consumer Goods, Retail, Manufacturing, or Financial Services.

Apply if you have:

• ~3 years of experience in Data Engineering or related fields (BI, Data Science).
• Hands‑on experience with Databricks, Snowflake, BigQuery, MS Fabric.
• Experience building data warehouses/lakehouses with Azure Data Factory / Synapse.
• Skills in PySpark/Python and SQL.
• Some exposure to CI/CD (Azure DevOps, Jira).
• B2+ English and ability to prepare technical documentation.
• Experience using modern tech and AI tools in daily work.

Nice to have:

• Cloud certifications (Azure/AWS/GCP) and Data Governance certifications.
• Training via platforms like Coursera/Udemy/Datacamp.
• Knowledge of data modelling (e.g., Kimball), Data Strategy, Data Quality, and MDM.
• Experience with Agile (Scrum), ML/GenAI use cases, or Agentic AI for data automation.
• Work with senior stakeholders (e.g., CDOs) in Manufacturing, Consumer Goods, or Financial Services.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

A leading organization in the media streaming industry focuses on delivering innovative solutions that enhance user engagement and content accessibility. The company caters to a diverse audience, including individual consumers and content creators, providing them with advanced tools for content production and distribution. With a strong emphasis on technology, the organization leverages cutting-edge AI and machine learning capabilities to optimize user experiences and operational efficiency. Their commitment to continuous improvement and adaptation positions them as a significant player in the evolving media landscape.

We are looking for an experienced Data Engineer to participate in desing and architectute of client's data platform and GenAI initiatives. The primary focus of this role is building scalable distributed data processing systems that will serve as the foundation for the company's intelligent services.



Job Description

Required:

• Bachelor’s/Master’s degree in Computer Science, Computer Engineering, Machine Learning, or a related field.
• 4+ years of experience in software development, focusing on Python programming and data engineering.
• Strong expertise in Data Lake architecture and modern data warehousing.
• Hands-on experience with distributed computing systems (Apache Spark is a must).
• Strong Python proficiency for building complex pipelines and internal tooling.
• Good understanding of distributed systems principles, real-time data processing, and batch processing.
• Experience in scaling data infrastructure (AWS/GCP cloud solutions).
• Proven experience in designing and scaling vector databases (e.g. Pinecone, Milvus, Weaviate, pgvector etc.), experience in developing recommendation systems and retrieval-augmented generation (RAG) pipelines.
• Ability to independently drive technical discussions, make informed architectural assumptions, and justify technology choices.
• Ability to decompose complex "from scratch" tasks without detailed specifications.

Nice to have:

• Intermediate knowledge of Airflow for workflow management in data processing.
• Generative AI: Experience with vector databases, RAG architectures, or integrating LLMs into data pipelines.
• Experience designing and building middleware platforms, REST APIs, and distributed systems at scale.
• Web Development: Basic API development skills to provide data access to other services.

Job Responsibilities

• Data Platform: Designing and maintaining high-load Spark pipelines for processing terabytes of data.
• GenAI Support: Building data infrastructure for training and operating generative models (ingestion, cleaning, vectorization).
• Architectural Contribution: Active participation in technical brainstorming, developing data quality standards, and processing protocols.
• Optimization: Identifying and resolving bottlenecks in current distributed processing systems.