Jobs Data Engineer

Google Cloud Solutions Architect / Pre-Sales Engineer

Company: Softprom Solutions
Location: Remote (Ukraine)
Employment: Full-time, FOP (contractor)

About the role

Softprom Solutions is looking for a Google Cloud Solutions Architect / Pre-Sales Engineer to join our Cloud team.

This role is ideal for a specialist with hands-on experience in Google Cloud Platform and an active Google Cloud certification, who wants to work on real commercial projects, participate in pre-sales activities, and grow in cloud architecture.

Responsibilities

• Design and document Google Cloud architectures according to the Google Cloud Architecture Framework
• Participate in pre-sales activities:
  • technical discovery with customers
  • solution design
  • participation in demos and presentations
• Deployment and configuration of core GCP services, including:
  • Compute Engine, Cloud Storage, Cloud SQL
  • VPC, IAM, Load Balancing
  • Cloud Functions / Cloud Run
• Design and configure GCP networking:
  • VPC networks, subnets
  • Firewall rules
  • Routes
• Implement and support Infrastructure as Code (IaC) using Terraform
• Create technical and solution documentation
• Act as a technical point of contact for sales and customers

Requirements (Must have)

• Active Google Cloud certification
  (Associate Cloud Engineer or Professional Cloud Architect)
• Experience as Cloud Engineer / Solutions Architect / Pre-Sales Engineer
• Practical understanding of Google Cloud core services:
  • Compute, Storage, Databases, Networking, Security
• Solid networking knowledge:
  • TCP/IP (L3, L4)
  • IP addressing, subnetting
  • DNS
• Understanding of cloud principles:
  • High Availability
  • Fault Tolerance
  • Scalability
  • Security
• Linux skills (command line)

Nice to have

• Experience in pre-sales or customer-facing roles
• Experience with Terraform
• Basic scripting skills (Python, Bash)
• Experience with Docker, Kubernetes (GKE), Cloud Run
• Experience with AWS or multi-cloud environments

Soft skills

• Ability to communicate technical solutions to non-technical audiences
• Structured and analytical thinking
• Proactivity and ownership
• Ukrainian — fluent
• English — reading and basic spoken (technical / pre-sales)

We offer

• Compensation: $2000 USD + project-based bonuses
• FOP cooperation
• Full-time workload
• Real commercial Google Cloud projects
• Participation in pre-sales and architecture design
• Professional growth in Cloud & Solutions Architecture
• International projects and vendors
• Strong cloud team and mentorship

AWS Cloud Engineer

Softprom Solutions
Azerbaijan | Remote / Hybrid
Full-time | Contractor (Individual Entrepreneur)
Contract with Austria

About Softprom

Softprom Solutions is an international IT distributor and solutions provider working with leading global vendors in Cloud, Cybersecurity, Infrastructure, and Enterprise IT.

We are expanding our Cloud Practice and are looking for an AWS Cloud Engineer in Azerbaijan who wants to grow professionally, work on real customer projects, and collaborate with international teams under an Austrian contract.

About the role

This role is ideal for an AWS-certified engineer with solid fundamentals who wants to deepen hands-on experience in cloud architecture, deployments, automation, and customer-facing work.

You will work closely with senior architects, sales teams, and customers, participating in both technical delivery and pre-sales activities.

Responsibilities

• Support the design and documentation of AWS cloud architectures following the AWS Well-Architected Framework
   
• Participate in deployment and configuration of core AWS services, including
  VPC, EC2, S3, RDS, IAM, Lambda, Load Balancers
   
• Assist with AWS networking configuration:
  Subnets, Route Tables, Security Groups, NACLs
   
• Contribute to automation and Infrastructure as Code (IaC) initiatives using
  Terraform and/or AWS CloudFormation
   
• Create and maintain technical documentation for architectures and configurations
   
• Participate in customer meetings, presentations, and demos, explaining AWS solutions and capabilities
  
   

Requirements (Must have)

• Active AWS Certified Solutions Architect – Associate (SAA-C03)
   
• Solid theoretical understanding of AWS core services:
  Compute, Storage, Databases, Networking, Security
   
• Basic networking knowledge:
  TCP/IP (L3, L4), IP addressing, subnetting, DNS
   
• Understanding of cloud principles:
  High Availability, Fault Tolerance, Scalability, Security
   
• Basic Linux skills (command line)
   
• Ability to read and understand technical documentation in English
  
   

Nice to have

• Hands-on experience with Terraform or CloudFormation
   
• Basic scripting skills (Python, Bash)
   
• Familiarity with Docker, Kubernetes, ECS
   
• Personal, educational, or non-commercial projects deployed on AWS
  
   

Soft skills

• Strong motivation to learn and grow in cloud engineering
   
• Structured and analytical thinking
   
• Clear and confident communication
   
• Ukrainian or Russian — fluent
   
• English — reading technical documentation (spoken English is a plus)
  
   

We offer
 

• Individual Entrepreneur (FOP) / contractor model
   
• Official contract with Austria
   
• Full-time workload
   
• Real commercial AWS projects (not internal labs)
   
• Participation in architecture design and pre-sales activities
   
• Professional growth within Cloud & Solutions Architecture
   
• International customers and vendors
   
• Supportive, senior cloud team and mentorship

Description:

Our Client is the fast-paced digital healthcare company which creates the growing portfolio of online health communities for people with chronic conditions. Company’s mission is to improve patient’s 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 re-design and enhance data-driven solutions. The team is responsible for expanding and optimizing the data flow and data pipeline architecture, model and analyze data, interpret trends or patterns in complex data sets and translate 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:

● Good Python skills

● Good 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, Elasticsearch Service, Route 53, VPC, etc
• Snowflake
• Docker
• dbt
• Airflow
   

Job responsibilities:

● Manage and optimize core data infrastructure

● Develop 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

● Build and maintaining custom ingestion pipelines

● Build non-SQL transformation pipelines

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

We are looking for a Data Engineer to join our team!

Data Engineer is responsible for designing, maintaining, and optimizing data infrastructure for data collection, management, transformation, and access.

He/she will be in charge of creating pipelines that convert raw data into usable formats for data scientists and other data consumers to utilize.

Data Engineer should be comfortable working with RDBMS and has a good knowledge of the appropriate RDBMS programming language(s) as well.

The Data Engineer fulfills processing of client data based on proper specification and documentation.

     Main responsibilities:

• Design and develop ETL pipelines;
• Data integration and cleansing;
• Implement stored procedures and function for data transformations;
• ETL processes performance optimization.

     Skills and Requirements:

• Experience with ETL tools (to take charge of the ETL processes and performs tasks connected with data analytics, data science, business intelligence and system architecture skills);
• Database/DBA/Architect background (understanding of data storage requirements and design warehouse architecture, should have the basic expertise with SQL/NoSQL databases and data mapping, the awareness of Hadoop environment);
• Data analysis expertise (data modeling, mapping, and formatting, data analysis basic expertise is required);
• Knowledge of scripting languages (Python is preferable);
• Troubleshooting skills (data processing systems operate with large amounts of data and include multiple structural elements. Data Engineer is responsible for the proper functioning of the system, which requires strong analytical thinking and troubleshooting skills);
• Tableau experience is good to have;
• Software engineering background is good to have;
• Good organizational skills, and task management abilities;
• Effective self-motivator;
• Good communication skills in written and spoken English.

     Salary Range

Compensation packages are based on several factors including but not limited to: skill set, depth of experience, certifications, and specific work location.

About the client
Haptiq is an AI-native enterprise solutions company with purpose-built technology for public & private companies, governments, institutions, asset managers, and family offices

With headquarters in New York City and four global offices, Haptiq is supported by more than 300 engineers and delivery professionals across the globe. By centralizing and unifying data, automating workflows, and surfacing predictive insights, Haptiq enables organizations to scale operational excellence and generate alpha across complex enterprise environments

The Opportunity
This position is for a Cloud Data Engineer with a background in Python, DBT, SQL, and data warehousing for enterprise-level systems
 

Responsibilities and Duties
— Design, develop, and deploy Python scripts and ETL processes with Prefect and Airflow to prepare data for analysis
— Model dimensional and denormalized schemas for optimal performance reporting and discovery
— Design AI-friendly DB schemas and ontologies
— Architect cloud ops solutions for data topologies
— Transform and migrate data with Python, DBT, and Pandas
— Work with event-based/streaming technologies for real-time ETL
— Ingest and transform structured, semi-structured, and unstructured data
— Optimize ETL jobs for performance and scalability to handle big data workloads
— Monitor and troubleshoot ETL jobs to identify and resolve issues or bottlenecks
— Implement best practices for data management, security, and governance with Prefect, DBT, and Pandas
— Write SQL queries and program stored procedures and reverse engineer existing data pipelines
— Perform code reviews to ensure fit to requirements, optimal execution patterns, and adherence to established standards
— Assist with automated release management and CI/CD processes
— Validate and cleanse data and handle error conditions gracefully
 

Requirements
— 3+ years of Python development experience, including Pandas
— 5+ years writing complex SQL queries with RDBMSes
— 5+ years of Experience with developing and deploying ETL pipelines using Airflow, Prefect, or similar tools
— Experience with cloud-based data warehouses in environments such as RDS, Redshift, or Snowflake
— Experience with data warehouse design: OLTP, OLAP, Dimensions, and Facts
— Experience with cloud-based data architectures, messaging, and analytics
— Bachelor’s degree in Computer Science or equivalent — preferred
 

Pluses — Experience with
— Docker
— Kubernetes
— CI/CD automation
— AWS lambdas/step functions
— Data partitioning
— Databricks
— Pyspark
— Cloud certifications
 

Why Join Us?
We value creative problem solvers who learn fast, work well in an open and diverse environment, and enjoy pushing the bar for success ever higher. We do work hard, but we also choose to have fun while doing it

We are looking for a Data Engineer to join our partner team.

The primary goal of this role is to design, build, and maintain a scalable data infrastructure that supports analytics, reporting, and data-driven decision-making across the organisation.

This role focuses on developing reliable data pipelines, integrating multiple data sources, ensuring data quality, and delivering business-oriented data solutions aligned with company goals.

What you will do:

• Development and maintenance of ELT processes for collecting, transforming, and loading data from various sources into BigQuery.
• Creation and development of a dbt project to build data models (stage, base, intermediate, dimension, report layers) used in analytics and reporting.
• Optimization of performance of pipelines, SQL queries, and data models.
• Validation, testing, and data quality control at all stages of the pipeline.
• Setting up monitoring and alerting for data pipelines and key infrastructure components.
• Integration of data from various sources (mobile application, financial and marketing information), including APIs and external systems.
• Collaboration with analysts to ensure data is properly structured, easy to use, and supports the team’s analytical needs.
• Maintaining up-to-date documentation regarding data architecture, ELT processes, and dbt models.
• Tools you will work with: SQL, Python, dbt, and GCP cloud services for building and maintaining data pipelines.

What we expect from you:

• 3+ years of experience in a Data Engineer position or a related role with a strong focus on building pipelines and data modeling.
• Deep knowledge of SQL: complex queries, optimization, understanding of Data Warehousing principles.
• Practical experience working with BigQuery, Snowflake, Redshift, or other analytical warehouses.
• Experience working with dbt, including testing, documentation, and CI/CD integration.
• Experience building and maintaining ELT/ETL pipelines.
• Strong proficiency in Python for integrations, automation, and data processes.
• Confident use of Git and experience working with GitHub/GitLab.
• Experience working with GCP or other cloud platforms.
• Attention to detail, strong problem-solving mindset, and ownership of results.
• Experience collaborating with analysts and understanding their data needs.
• Nice to have:
• Experience optimizing cost efficiency and query performance in cloud environments.
• Experience working with real-time / streaming data solutions.
• Ability to clearly explain technical solutions to stakeholders.

Hi there! AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

Why join us
If you’re looking for a place to grow, make an impact, and work with people who care, we’d love to meet you! :)

About the role
As a Data Steward, you will play a key role in ensuring high-quality, reliable product data that directly impacts sales performance across the EMEA market. This role sits at the intersection of business and technology, shaping how product information flows through PIM systems and reaches external channels. You’ll have real influence on data standards, processes, and visibility, while collaborating with diverse stakeholders in a structured yet supportive environment. It’s an opportunity to grow your expertise in data stewardship, product information management, and cross-functional collaboration within a global setup.

What you will do
● Validate that mandatory product data provided by business teams is accurate and complete;
● Upload product data into the PIM system and resolve data gaps, including coordinating with multiple stakeholders to complete missing information;
● Syndicate product data into channel-specific templates and resolve any related issues;
● Support business teams when they encounter issues using product data for the channel;
● Clarify and communicate data issues and requirements to stakeholders to ensure data quality and accuracy;
● Create, track, and report on the status of product data requests;
● Reconfigure and maintain syndication templates in inRiver.

Must haves
● Minimum of 3 years of experience in data management, with solid knowledge of core principles and concepts;
● Good understanding of the data lifecycle;
● Ability to use multiple tools to create and maintain data stewardship processes, inputs, and outputs;
● Hands-on experience with Inriver is required; alternatively, experience with Salsify, Informatica, or Akeneo (in complex implementations) will be considered;
● Experience working with retailers and marketplaces, including PIM syndication setup and management;
● Strong Excel skills;
● Ability to work efficiently under tight and ongoing deadlines;
● Strong communication skills, with the ability to interact with both business and technical stakeholders;
● Fluent written and spoken English.

Perks and benefits
● Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
● Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
● A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
● Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office — whatever makes you the happiest and most productive.


Meet Our Recruitment Process
Asynchronous stage — An automated, self-paced track that helps us move faster and give you quicker feedback:
● Short online form to confirm basic requirements
● 30–60 minute skills assessment
● 5-minute introduction video
Synchronous stage — Live interviews
● Technical interview with our engineering team (scheduled at your convenience)
● Final interview with your future teammates
If it’s a match—you’ll get an offer!

Department/Project Description

Project aims to integrate a data-driven Markdown Optimization module and enhance Promotions Forecasting within clients' Price Index Management (PIM) to maximize gross profit, sell-through, and capture rate while maintaining price image. It will automate pricing recommendations based on inventory, generate accurate demand forecasts, and improve markdown/promotional strategies through user-friendly workflows.
GlobalLogic will develop the backend, data science, and UI/UX for this standalone application.

Job Responsibilities

• Build and maintain data pipelines adhering to the suggested enterprise architecture principles and guidelines
• Collect and manage data, converting it into useful information
• Work on the optimisation of partitioning and clustering for selected tables
• Implementation of data retention policies and removal of unused/dormand tables
• Work on the various optimisations
• Design, build, test, and maintain data management systems
• Work in sync with internal and external team members like data architects, data scientists, data analysts to handle all sorts of technical issue
• Deliver quality deliverables on time
• Translate complex functional requirements into technical solutions.

Job Description

• 5+ years of experience in Data Engineering
• Creation and maintenance of optimum data pipeline architecture for the ingestion and processing of data
• Creation of necessary infrastructure for ETL jobs from a wide range of data sources
• Experience in Snowflake cost optimisation, query pruning, and performance tuning
• Experience in Data storage technologies
• Upper Intermediate level of English
• Experience with GCP
• Good experience developing ETL pipeline using DBT
• Good Communication skills
• Willing to learn new technologies, share your ideas and assist other team members as needed
• Strong analytical and problem-solving skills; ability to define problems, collect data, establish facts, and draw conclusions

✨ About us   

code.store is a French software services company on a mission to enhance business operations by building smart, lean software. We use AI agents, low-code platforms, and SaaS tools to deliver solutions that are fast, efficient, and truly owned by our clients — no technical debt, no long-term dependencies.

We’re both a consulting partner and a delivery powerhouse. That means we don’t just build what clients ask for, we dig deep to understand how they work and how we can help them work better.

🏠 Offices

Our company is headquartered in Paris, yet our tech team operates remotely.

⚡Our Values

• Excel at what we do
• Provide the best technical and functional quality to our clients
• Kindness, honesty, fun, and trust
• Stay curious and always keep learning
   

✏️ Your responsibilities

• Own the end-to-end design and implementation of the Modern Data Stack in a highly fragmented and low-maturity environment
• Build a production-grade data foundation from scratch, ensuring reliability, scalability, and fast time-to-value
• Integrate and reconcile multiple data sources (CRM Batch, Piano, WordPress, analytics tools) into a single source of truth
• Design and implement a robust data warehouse architecture aligned with business-critical use cases
• Develop, optimize, and orchestrate resilient data pipelines (Airbyte, SQL, orchestration tools)
• Define and implement a Master Data Management approach (Golden Record / Master ID) across inconsistent data sources
• Take full ownership of data quality, including monitoring, validation, and continuous improvement processes
• Translate ambiguous business needs into clear, scalable data models (users, subscribers, interactions, churn signals)
• Deliver ready-to-use datasets for churn prediction, segmentation, and CRM activation under tight timelines
• Make and defend architecture and tooling decisions, balancing speed vs long-term sustainability
• Ensure data is actionable and accessible for data science, product, and business stakeholders
• Enable daily operational use cases (e.g., churn scoring, CRM automation) with high reliability
• Proactively communicate trade-offs, risks, and limitations to both technical and non-technical stakeholders

🎯 You’re the right candidate if you have

• 4+ years of hands-on experience in data engineering within Modern Data Stack environments
• 4+ years of deep experience with advanced SQL and data transformation at scale
• 4+ years of experience building robust, production-grade data pipelines (ETL/ELT)
• Proven experience with data warehouse architecture (BigQuery, Snowflake, Redshift, or equivalent)
• Strong understanding of data modeling (analytical & operational) and data system design
• Solid experience with data quality frameworks, MDM, and identity resolution in complex environments
• Practical understanding of business-driven use cases (churn, engagement, CRM, segmentation)
• Ability to work autonomously in low-structure, high-ambiguity environments
• Strong ownership mindset with a focus on delivering business impact, not just technical output
• English proficiency at B2 level or above
   

🧩 Will be a big plus

• Experience working in subscription-based businesses, digital media, or marketing-driven organizations
• Proven track record of building a data platform from scratch under time and resource constraints
• Hands-on experience with Airbyte, dbt, and modern orchestration tools
• Experience integrating with CRM and product analytics platforms (e.g., Batch, Piano, similar)
• Exposure to churn modeling pipelines, feature engineering, and production ML/data science workflows

💻 Tech stack on different projects

Backend: Xano (low-code back-end as a service, database, and API layer), NestJS, Node.js, TypeScript, TRPC

Frontend: Next.js, Custom React frontends (some Content Management Systems provide their own

🤝Hiring process

• 1h interview with HR and a technical prescreening in English. Please note that your answers will be recorded on video and shared with our tech team for further review
•  1.5h Technical interview 
• 30 min interview with CTO

Main Responsibilities:

Data Engineer is responsible for helping select, deploy, and manage the systems and infrastructure required of a data processing pipeline to support customer requirements.

You will work on cutting-edge cloud technologies, including Microsoft Fabric, Azure Synapse Analytics, Apache Spark, Data Lake, Data Bricks, Data Factory, Cosmos DB, HD Insights, Stream Analytics, Event Grid in the implementation projects for corporate clients all over EU, CIS, United Kingdom, Middle East.

Our ideal candidate is a professional passionated with technologies, a curious and self-motivated person.

Responsibilities revolve around DevOps and include implementing ETL pipelines, monitoring/maintaining data pipeline performance, model optimization

Mandatory Requirements:

– 3+ years of experience, ideally within a Data Engineer role.

– understanding of data modeling, data warehousing concepts, and ETL processes

– 2+ years of experience with Azure Cloud technologies

– experience in distributed computing principles and familiarity with key architectures, broad experience across a set of data stores (Azure Data Lake Store, Azure Synapse Analytics, Apache Spark, Azure Data Factory)

– Understanding of landing, staging area, data cleansing, data profiling, data security and data architecture concepts (DWH, Data Lake, Delta Lake/Lakehouse, Datamart)

– SQL-skills

– communication and interpersonal skills

– English —В2

Will be beneficial if a candidate has experience in SQL migration from on-premises to cloud, data modernization and migration, advanced analytics projects, and/or professional certification in data&analytics.

We offer:

– professional growth and international certification

– free of charge technical and business trainings and the best bootcamps (worldwide, including HQ Microsoft- Redmond courses)

– innovative data & analytics projects, practical experience with cutting-edge Azure data&analytics technologies at various customers’ projects

– great compensation and individual bonus remuneration

– medical insurance

– long-term employment

– ondividual development plan

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.

Skills

Must have

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

Cloud certifications is a plus

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

We are seeking a Senior Database Engineer for a short-term, part-time project to refine our data infrastructure. You will architect a scalable analytics foundation and optimize transactional performance for a platform trusted by 300+ industry leaders. This role offers full technical ownership and a skip-the-bureaucracy environment, allowing you to implement your own expert recommendations. It is a perfect high-impact contract for those who value professional autonomy and a flexible schedule

A new team member will be in charge of:

• Designing and standing up a reporting/analytics data warehouse (preferably on Azure) to support business intelligence and analytical workloads.
• Defining dimensional and/or analytical schemas that enable reliable reporting and scalable querying.
• Building and maintaining data pipelines to move and transform data from source systems into the warehouse (e.g., using Azure Data Factory / Synapse or similar).
• Auditing and improving indexing strategy for Azure SQL / SQL Server to ensure consistent performance at scale.
• Optimizing queries through execution plan analysis, refactoring, and targeted tuning.
• Designing and implementing caching strategies where appropriate to reduce load and improve response times.
• Applying partitioning and sharding approaches when needed to support growth and throughput.
• Improving schema design for performance, maintainability, and long-term evolution of the product.
• Designing and optimizing complex indexed views and other advanced SQL Server features.
• Collaborating with a technical team by clearly communicating findings, trade-offs, and implementation plans.

Does this relate to you?

• 5+ years of commercial experience in database engineering, data warehousing, or a similar role.
• Strong SQL Server / Azure SQL expertise, including performance tuning, schema design, and execution plan analysis.
• Hands-on experience with Azure data services such as Azure SQL, Azure Data Factory, Synapse, or equivalent tools.
• Proven experience designing and building data warehouses and analytics-ready data models.
• Ability to work independently end-to-end: assessing current state, making recommendations, and executing implementations.
• Strong communication skills with the ability to explain technical findings and recommendations to a technical audience.
• Experience with SaaS transactional databases at scale is a plus.
• Azure AI Search experience (implementing or designing search solutions) is strongly preferred.
• Familiarity with vector databases, especially for AI/ML workloads, is a plus.
• Supporting search and AI-driven use cases by contributing to Azure AI Search design/implementation (preferred) and exploring vector database approaches (a plus).

Department/Project Description

Project aims to integrate a data-driven Markdown Optimization module and enhance Promotions Forecasting within clients' Price Index Management (PIM) to maximize gross profit, sell-through, and capture rate while maintaining price image. It will automate pricing recommendations based on inventory, generate accurate demand forecasts, and improve markdown/promotional strategies through user-friendly workflows.
GlobalLogic will develop the backend, data science, and UI/UX for this standalone application.

Job Responsibilities

• Build and maintain data pipelines adhering to the suggested enterprise architecture principles and guidelines
• Collect and manage data, converting it into useful information
• Work on the optimisation of partitioning and clustering for selected tables
• Implementation of data retention policies and removal of unused/dormand tables
• Work on the various optimisations
• Design, build, test, and maintain data management systems
• Work in sync with internal and external team members like data architects, data scientists, data analysts to handle all sorts of technical issue
• Deliver quality deliverables on time
• Translate complex functional requirements into technical solutions.

Job Description

• 5+ years of experience in Data Engineering
• Creation and maintenance of optimum data pipeline architecture for the ingestion and processing of data
• Creation of necessary infrastructure for ETL jobs from a wide range of data sources
• Experience in Snowflake cost optimisation, query pruning, and performance tuning
• Experience in Data storage technologies
• Upper Intermediate level of English
• Experience with GCP
• Good experience developing ETL pipeline using DBT
• Good Communication skills
• Willing to learn new technologies, share your ideas and assist other team members as needed
• Strong analytical and problem-solving skills; ability to define problems, collect data, establish facts, and draw conclusions

Engagement Terms: Full-time (~40 hrs/week) | 6-month initial contract (extension possible) 
Timezone Requirement: Strict overlap with U.S. working hours (EST–PST)
Availability: Immediate start or short notice / bench availability required
Schedule Constraint: Full-time only; no part-time or non-overlapping schedules

Role Summary

We are seeking a Senior Data Engineer to join a high-growth SaaS environment focused on building scalable data infrastructure and enabling ML/analytics workflows. The role is centered on designing and maintaining robust data platforms, supporting real-time and batch processing systems, and enabling data science and machine learning initiatives.

Technical Requirements (Recent 2–3 Years Hands-On Experience)

• Data Engineering: Apache Kafka (streaming), Apache Airflow (orchestration), advanced SQL, NoSQL databases
• Cloud & APIs: Strong AWS experience (preferred), API development experience
• Infrastructure: Docker, Kubernetes, Terraform / CloudFormation (IaC)
• CI/CD: Experience building and maintaining deployment pipelines
• Observability & Governance: Monitoring, logging, data quality, and governance frameworks

• Nice to have: ML pipelines, AWS SageMaker, OpenAI or LLM-based integrations

   

Key Responsibilities

• Design and implement scalable batch and streaming data pipelines
• Build and evolve data platform infrastructure supporting analytics and ML use cases
• Develop event-driven architectures using Kafka and secure API systems
• Collaborate closely with Data Science and ML teams to enable production-ready workflows

• Ensure data reliability, observability, governance, and system performance across platforms

   

Candidate Profile

• Proven expertise in Kafka, Airflow, and AWS-based architectures
• Experience building production-grade data platforms at scale
• Strong understanding of distributed systems and event-driven design
• Ability to work in fast-paced, product-driven environments