Jobs Data Engineer

Senior Data Engineer

About the Company

Our company is a leading technology provider specializing in data-driven solutions that help businesses transform their operations and generate insights from complex datasets. We work with clients across various industries globally, building scalable and efficient data infrastructure that powers business intelligence and analytics.

Work Format

• 100% Remote Work
• Flexible schedule
• Opportunity to work from any location

Responsibilities

• Design, build, and maintain scalable data processing pipelines and ETL workflows
• Develop data models and implement data warehousing solutions
• Create and optimize database schemas and queries for performance
• Integrate diverse data sources and ensure data quality and consistency
• Implement and manage big data processing systems using modern technologies
• Collaborate with data scientists and analysts to understand data requirements and provide solutions
• Build data monitoring and validation systems to ensure data integrity
• Design and implement data governance practices and documentation
• Optimize data architecture for cost, reliability, and performance
• Participate in code reviews and mentor junior engineers

Requirements

Mandatory

• 5+ years of experience in data engineering roles
• Strong expertise in SQL and database design (SQL Server, PostgreSQL, MySQL)
• Proficiency in Python and data processing libraries (Pandas, NumPy)
• Experience with ETL tools and frameworks (Airflow, Informatica, Talend, etc.)
• Hands-on experience with big data technologies (Hadoop, Spark, Kafka)
• Knowledge of data warehousing concepts and technologies (Snowflake, Redshift, BigQuery)
• Experience with cloud platforms (AWS, Azure, or GCP) and their data services
• Understanding of data modeling techniques and best practices
• Experience with version control systems (Git) and CI/CD pipelines
• Strong problem-solving skills and attention to detail

Advantages

• Experience with real-time data processing and streaming architectures
• Knowledge of data visualization tools (Tableau, Power BI, Looker)
• Experience with NoSQL databases (MongoDB, Cassandra, Redis)
• Background in implementing data lakes and data mesh architectures
• Knowledge of ML/AI data pipelines and feature engineering
• Experience with infrastructure as code (Terraform, CloudFormation)
• Containerization and orchestration experience (Docker, Kubernetes)
• Experience with graph databases
• Open-source contributions to data engineering projects

Soft Skills

• Excellent communication and ability to explain complex technical concepts to non-technical stakeholders
• Strong collaboration skills for cross-functional teamwork
• Self-motivated with ability to work independently in a remote environment
• Analytical thinking and methodical approach to problem-solving
• Adaptability and eagerness to learn new technologies
• Proactive attitude toward identifying and addressing data issues

We Offer

• Competitive salary (based on experience and skills)
• Modern tech stack and opportunity to work with cutting-edge data technologies
• Clear career progression path
• Additional paid time off
• Regular virtual team-building activities
• Opportunity to work on challenging data projects across various industries

If you're passionate about building robust data systems and want to join a team that values innovation and engineering excellence, we'd love to hear from you. Please submit your resume with relevant experience and projects for consideration.

About Us:

Time2Mobile is a tech-driven team focused on building flexible digital solutions for fintech, e-commerce, logistics, and beyond. We work with data at every stage — from collection to analytics — developing robust infrastructures that power smart, data-driven decisions.

We're currently looking for a Middle Data Engineer to join our team and help build and scale our data systems and pipelines.

Your Responsibilities:

• Design, develop, and maintain ETL/ELT data pipelines
• Work with cloud data platforms (AWS, GCP, or Azure)
• Build and maintain data warehouse/lakehouse solutions
• Collaborate closely with data analysts, data scientists, and backend engineers
• Ensure data quality, implement monitoring and logging
• Participate in architectural and technical decision-making

What We Expect:

• 2+ years of experience as a Data Engineer
• Strong knowledge of databases (SQL, PostgreSQL, BigQuery, etc.)
• Hands-on experience with orchestration tools (Airflow, Prefect, or similar)
• Proficiency in Python for data-related tasks
• Understanding of data warehouse/lakehouse architectures
• Familiarity with scalable data infrastructure best practices
• CI/CD experience is a plus
• English level: Intermediate or higher (for documentation and internal communication)

What We Offer:

• Fully remote position
• Flexible working hours
• Paid vacation
• Professional growth and development opportunities
• Projects involving modern tools and data stacks
• A supportive and skilled team environment

Description

GlobalLogic is partnering with a US-based digital health company, whose mission is to connect people in social interactions for health conversations, build online health communities to support each other, and share knowledge about how to deal with the disease

About the client:

Our Client is a fast-paced digital healthcare company that creates a growing portfolio of online health communities for people with chronic conditions. The company’s mission is to improve patients’ quality of life by connecting them with each other, with caregivers, and healthcare industry partners, building beneficial social interactions and meaningful health conversations. 

About the project:
The core of the project is working with the data; the target is to redesign and enhance data-driven solutions. The team is responsible for expanding and optimizing the data flow and data pipeline architecture, modeling and analyzing data, interpreting trends or patterns in complex data sets, and translating them into product and marketing insights. If you are excited by the prospect of optimizing or even re-designing our data architecture to support our next generation of products and data initiatives, we would be thrilled to have you apply!

Requirements

● Strong Python skills

● Strong communication skills

● Strong working SQL knowledge and experience working with relational databases, query authoring (SQL), as well as working familiarity with a variety of databases

● A successful history of manipulating, processing, and extracting value from large disconnected datasets

● Experience building and optimizing data pipelines, architectures, and data sets

● Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

● Strong analytic skills related to working with unstructured datasets

Technologies:

• Python
• AWS: SES, RDS (MySQL), EC2, ECS, VPC, etc
• Snowflake
• Docker
• dbt
• Airflow

Job Responsibilities

● Manage and optimize core data infrastructure

● Develop a custom data infrastructure not available off-the-shelf

● Build monitoring infrastructure to give visibility into the pipeline’s status

● Monitor all jobs for impact on cluster performance

● Run maintenance routines regularly

● Tune table schemas to minimize costs and maximize performance

● Building and maintaining custom ingestion pipelines

● Build non-SQL transformation pipelines

● Build processes supporting data transformation, data structures, metadata, dependency, and workload management

Who we are

Big Sister AI is building the Sales Score standard — an objective 0-100 rating of sales execution quality. Think Moneyball for sales. Austin-based, Capital Factory portfolio, backed by AWS and Microsoft for Startups.
 

Why this role exists

We're migrating our entire data and audio pipeline to AWS — replacing our current toolstack with a production-grade, multi-tenant architecture. You'll own this build end-to-end.
 

What you'll own

• Design and build cloud-native data and audio processing pipelines on AWS
• Integrate Azure AI services for transcription and LLM scoring
• Own data layer architecture — reliability, schema design, cost optimization
• Build and maintain third-party connector integrations (CRM, notetakers)
• Actively use AI coding tools (Claude, Cursor, Copilot) — hard requirement, not nice-to-have
   

What you need

• Strong AWS hands-on: Lambda, S3, EventBridge, API Gateway, DynamoDB, Secrets Manager
• Azure experience: OpenAI endpoints, Speech Services, Function Apps
• Python 3 — serverless functions, adapters, webhook handlers
• PostgreSQL + SQL — solid data modeling fundamentals
• ELT experience with Data Clouds — Snowflake preferred, BigQuery or Redshift acceptable
• dbt — data modeling and transformation pipelines, production experience required
• Multi-cloud exposure: AWS primary, GCP (BigQuery) and Azure interaction expected
• Self-sufficient — delivers projects with minimal supervision, owns outcomes not just tasks
• Proactive AI tool user — you use Claude/Cursor daily, not occasionally
• Upper-intermediate English — async written communication with US team
• Ukrainian-based — Kyiv/Lviv timezone preferred
   

Nice to have

• AppFlow, Glue, Athena
• OAuth/credential management tools
• Experience working with US-based or distributed teams
   

What we offer

• Competitive Ukrainian market salary
• Direct collaboration with the CEO and US-based advisors
• Greenfield build — you're not inheriting legacy, you're replacing it
• Equity conversation after 3-month trial

EST working hours!!!

CrunchCode — міжнародна сервісна ІТ-компанія з досвідом близько 7 років у розробці вебсервісів і вебзастосунків. Ми працюємо у форматах staff augmentation (outstaff) та outsourcing і підключаємо спеціалістів до проєктів клієнтів у довгостроковій моделі співпраці.

Ми працюємо переважно з проєктами в доменах логістики (включно з last mile),e-commerce, fintech та банкінгу, а також enterprise-рішеннями.
Для нас важливо, щоб проєкт був “чистим” і зрозумілим з точки зору етики та цінності для користувачів.

Ми принципово не беремо проєкти, пов’язані з:
● gambling / гемблінгом,
● adult-контентом та порнографією,
● шахрайством або будь-якою розробкою, що спрямована на обман чи маніпуляції.

What We Offer:
● Fully remote work
● Long-term, stable project
● High level of autonomy and trust
● Minimal bureaucracy
● Direct impact on business-critical logistics systems
● Long-term engagement, not a short-term contract.

Required:
Senior Software / Data Engineer, English B2+
Full-time, EST working hours

Tech Stack:
Python 3.10.x, PySpark, Airflow, Pandas, AWS (ECS, Lambda, SQS, SNS,
ElastiCache, CloudWatch), Delta Lake, Databricks, MySQL (Aurora),
Terraform, Datadog, pytest.
 

Team:
ML Data Engineering — 9 members
2-week sprints: kickoff Monday evenings / demo Friday evenings (EST)

Requirements (Must-have):
- 7+ years of professional software engineering experience.
- Strong proficiency in Python (3.10.x).
- Expertise in large-scale event-driven and distributed system design.
- Strong AWS experience: ECS, Lambda, SQS, SNS, CloudWatch.
- Experience with data processing frameworks: Spark, Databricks.
- Hands-on experience with infrastructure-as-code (Terraform).
- Solid understanding of system performance, profiling, and optimization.
- Experience leading technical projects and mentoring engineers.
- Experience building and maintaining data-intensive backend systems or pipelines.

Responsibilities:
- Lead design and delivery of event-driven, distributed systems for large-scale
 metadata extraction, enrichment, and processing.
- Build and maintain scalable APIs and backend services for high-throughput
 content pipelines on AWS.
- Partner with Data Science, ML Engineering, Infrastructure, and Product teams
 to architect reliable, high-performance systems.
- Provide technical leadership and mentorship across the engineering org.
- Leverage AWS (ECS, Lambda, SQS, SNS, ElastiCache, CloudWatch) to deploy
 resilient production systems.
- Optimize existing systems for scalability, reliability, and performance.
- Ensure system health via monitoring, observability, and automated testing.
- Contribute to engineering strategy — identify gaps, propose initiatives,
 improve existing frameworks.

Nice to Have:
- Experience with Scala or Ruby.
- Experience with Airflow or similar workflow orchestration tools.
- Experience integrating ML or LLM-based models into production systems.
- Bachelor's degree in Computer Science or equivalent.

Hiring Process:
- Intro call
- Technical discussion
- Offer
Start: ASAP

About the Role

We are looking for a Data Engineer to design and implement scalable data pipelines that support Generative AI applications. You will work with large-scale datasets, optimize performance, and ensure seamless data integration across AI workflows.

Responsibilities:

• Design and develop scalable data pipelines to support AI/ML models.
• Work with structured and unstructured data for training and inference.
• Optimize ETL workflows for real-time and batch processing.
• Ensure data quality, governance, and security in cloud environments.
• Collaborate with AI/ML engineers to streamline data workflows.

• Deploy and manage data infrastructure on AWS, GCP, or Azure.

   

Requirements:

• 4+ years of experience in Data Engineering and Big Data technologies.
• Expertise in ETL pipelines, data warehousing, and distributed computing.
• Strong knowledge of SQL, NoSQL, and data lakes.
• Experience with cloud-based data services (AWS Glue, BigQuery, Azure Data Factory).
• Proficiency in Python, Spark, Kafka, Airflow.
• Experience with CI/CD, DevOps, and Agile methodologies.

What You’ll Get at Uvik:

• Generous paid time off: 18 vacation days + 12 sick leaves annually.
• Flexibility: manage your schedule, work fully remote, and keep a healthy work-life balance.
• Challenging projects: work with global clients and the latest technologies.
• Growth opportunities: we invest in your development and support career advancement.
• Competitive salary in a fast-growing international company.

Snowflake 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 Databricks Data Engineer to join our project and work on data-intensive client projects - think Data Lakehouses implementation , modernization, pipeline engineering or migrations.

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

WHAT WE EXPECT

Required:

• Strong SQL and Python - you write clean, production-grade code
• Experience with Databricks and Apache Spark - you know how it works under the hood and have solid experience
• Workflow orchestration with Airflow, Dagster, or equivalent
• Solid understanding of Data Engineering principles, Data Modelling, dimensional design, and best practices
• Experience with DWH, Medallion and Lakehouse architectures — you've designed or maintained one, not just heard the term
• Experience with one of the cloud provides AWS\Azure\GCP

Nice to Have:

• dbt
• Snowflake
• CI\CD

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.

Snowflake 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 Snowflake Data Engineer to join our project and work on data-intensive client projects - think DWH implementation , modernization, pipeline engineering or migrations.

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

WHAT WE EXPECT

Required:

• Strong SQL and Python - you write clean, production-grade code
• Experience with Snowflake - you know how it works under the hood and query optimization
• Workflow orchestration with Airflow, Dagster, or equivalent
• Solid understanding of Data Engineering principles, Data Modelling, dimensional design, and best practices
• Experience with DWH architectures — you've designed or maintained one, not just heard the term

Nice to Have:

• dbt
• Data Vault knowledge\experience

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.

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

We are looking for a hybrid profile combining Data Engineering and DevOps experience

The role is until April 2027 with potential extension.

The role is full time full remote for a Major international client.

To help you we need ideally a profile of Senior Data Engineer with Senior experience with Snowflake ETL/ELT pipeline,  data pipelines in production,  data warehouse,  data workflows,  Data Platform,  DevOps, cloud infrastructure, CI/CD AWS,  GIT, modern development ,  with Terraform or Docker

Data Engineer Snowflake with relevant experience with Data Platform
We are looking for a hybrid profile combining Data Engineering and DevOps experience.
Looking for someone with Senior capacity, at least 4 years of exp.as data engineer, someone who can thrive as part of a team, but can work independently.

Nothing specified as years of experience rather than 4+ general one. Still we are looking for people with senior capacity.
Only candidates with truly relevant and strong experience will be considered in the process. This will be assessed by our team
 

• Must to have relevant experience wih Snowflake
• Must to have relevant experience with ETL/ELT pipeline
• Must to have relevant experience with data pipelines in production
• Must to have relevant experience with data warehouse
• Must to have relevant experience with data workflows
• Must to have relevant experience with Data Platform
• Must to have relevant experience with DevOps
• Must to have relevant experience with cloud infrastructure
• Must to have relevant experience with Terraform or Docker
• Must to have relevant experience with CI/CD
• Must to have relevant experience with AWS
• Must to have relevant experience with GIT
• Must to have relevant experience with modern development workflows

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

You’ll be working on event-driven, distributed, and scalable systems in Python, building large-scale data and service pipelines on AWS that support project’s content enrichment and metadata systems. This is a long-term remote opportunity with a supportive international team and strong ownership from day one.
This is a long-term, fully remote opportunity with a supportive international team and plenty of room for ownership.

Client is an American ebook and audiobook subscription service that includes more than one million titles. They began as a site to host and share documents and has grown into a global digital library with over 1.5 million subscribers in nearly every country worldwide.
The team focuses on building scalable metadata pipelines that utilize traditional tools, in-house ML models, and LLMs. In this role, you’ll design and optimize large-scale data and service pipelines running on AWS, supporting project’s content enrichment and metadata systems. You’ll work closely with cross-functional teams to design reliable backend services that integrate machine learning models and LLM-based components when needed. This role offers the opportunity to work on cutting-edge generative AI and metadata enrichment problems at a truly global scale.

Platform Tech Stack:
Python 3.10.x, PySpark, Airflow, pytest, Pandas, AWS, Delta Lake, MySQL (Aurora), Databricks, Terraform, Datadog, AWS Lambda, ECS, SQS, SNS, ElastiCache, CloudWatch.

Responsibilities:
● Provide technical leadership, mentorship, and guidance to engineers across the organization, driving secure coding best practices
● Lead the design, implementation, and scaling of event-driven, distributed systems to extract, enrich, and process metadata from large-scale document and media datasets
● Partner with Data Science, Infrastructure, ML Engineering, and Product teams to architect and deliver robust systems that balance scalability, high performance, and rapid iteration
● Contribute to the team’s engineering strategy, identifying gaps, proposing new initiatives, and improving existing frameworks
● Build and maintain scalable APIs and backend services for high-throughput content processing
● Leverage AWS services such as ECS, Lambda, SQS, ElastiCache, and CloudWatch to design and deploy resilient, high-performance systems
● Optimize and refactor existing backend systems for scalability, reliability, and performance
● Ensure system health and data integrity through monitoring, observability, and automated testing

Required skills:
- 7+ years of experience as a professional software engineer
- Strong proficiency in Python
- Proven ability to lead the design and delivery of complex software systems with minimal supervision
- Expertise in designing and architecting large-scale event-driven and distributed systems
- Strong cloud expertise with AWS services such as ECS, Lambda, SQS, SNS, and CloudWatch
- Familiarity with data processing frameworks such as Spark and Databricks
- Experience with infrastructure-as-code tools like Terraform
- Solid understanding of system performance, profiling, and optimization
- Experience leading technical projects and mentoring engineers
- Experience building and maintaining data-intensive backend systems or pipelines
- Upper-Intermediate English or higher

Nice to Have:
● Experience with Scala
● Familiarity with Ruby
● Bachelor’s degree in Computer Science or equivalent professional experience
● Experience with workflow orchestration tools such as Airflow
● Experience integrating ML or LLM-based models into production systems


Working Conditions:
— Work schedule: EST working hours !!!!
— Fully Remote
— Engagement: Long-term
— Full-time workload
— 2-week sprints with kickoff on Monday evenings and demos on Friday evenings