Senior Azure Data Engineer with Databricks Job at DCG Sp. z o. o.

Senior ML Data Engineer

As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream,...

Location

Salary:

Not provided

Awin Global

Expiration Date

Until further notice

Requirements

Bachelor or Master’s degree in data science, data engineering, Computer Science with focus on math and statistics / Master’s degree is preferred
At least 5 years experience as AI/ML data engineer undertaking above task and accountabilities
Strong foundation in computer science principes and statistical methods
Strong experience with cloud technology (AWS or Azure)
Strong experience with creation of data ingestion pipeline and ET process
Strong knowledge of big data tool such as Spark, Databricks and Python
Strong understanding of common machine learning techniques and frameworks (e.g. mlflow)
Strong knowledge of Natural language processing (NPL) concepts
Strong knowledge of scrum practices and agile mindset

Job Responsibility

Design and maintain scalable data pipelines and storage systems for both agentic and traditional ML workloads
Productionise LLM- and agent-based workflows, ensuring reliability, observability, and performance
Build and maintain feature stores, vector/embedding stores, and core data assets for ML
Develop and manage end-to-end traditional ML pipelines: data prep, training, validation, deployment, and monitoring
Implement data quality checks, drift detection, and automated retraining processes
Optimise cost, latency, and performance across all AI/ML infrastructure
Collaborate with data scientists and engineers to deliver production-ready ML and AI systems
Ensure AI/ML systems meet governance, security, and compliance requirements
Mentor teams and drive innovation across both agentic and classical ML engineering practices
Participate in team meetings and contribute to project planning and strategy discussions

What we offer

Flexi-Week and Work-Life Balance: We prioritise your mental health and well-being, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves as well as volunteer days
Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately
Pension: Awin offers access to an additional pension insurance to all employees in Germany
Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions
Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development
Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program

Senior ML Data Engineer

As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream,...

Location

Poland , Warsaw

Salary:

Not provided

Awin Global

Expiration Date

Until further notice

Requirements

Bachelor or Master’s degree in data science, data engineering, Computer Science with focus on math and statistics / Master’s degree is preferred
At least 5 years experience as AI/ML data engineer undertaking above task and accountabilities
Strong foundation in computer science principes and statistical methods
Strong experience with cloud technology (AWS or Azure)
Strong experience with creation of data ingestion pipeline and ET process
Strong knowledge of big data tool such as Spark, Databricks and Python
Strong understanding of common machine learning techniques and frameworks (e.g. mlflow)
Strong knowledge of Natural language processing (NPL) concepts
Strong knowledge of scrum practices and agile mindset
Strong Analytical and Problem-Solving Skills with attention to data quality and accuracy

Job Responsibility

Design and maintain scalable data pipelines and storage systems for both agentic and traditional ML workloads
Productionise LLM- and agent-based workflows, ensuring reliability, observability, and performance
Build and maintain feature stores, vector/embedding stores, and core data assets for ML
Develop and manage end-to-end traditional ML pipelines: data prep, training, validation, deployment, and monitoring
Implement data quality checks, drift detection, and automated retraining processes
Optimise cost, latency, and performance across all AI/ML infrastructure
Collaborate with data scientists and engineers to deliver production-ready ML and AI systems
Ensure AI/ML systems meet governance, security, and compliance requirements
Mentor teams and drive innovation across both agentic and classical ML engineering practices
Participate in team meetings and contribute to project planning and strategy discussions

What we offer

Flexi-Week and Work-Life Balance: We prioritise your mental health and well-being, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves as well as volunteer days
Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately
Pension: Awin offers access to an additional pension insurance to all employees in Germany
Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions
Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development
Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program

Senior Data Engineer

Our client is a global jewelry manufacturer undergoing a major transformation, m...

Location

Poland , Wroclaw

Salary:

Not provided

Zoolatech

Expiration Date

Until further notice

Requirements

5+ years of experience as a Data Engineer with proven expertise in Azure Synapse Analytics and SQL Server
Advanced proficiency in SQL, covering relational databases, data warehousing, dimensional modeling, and cubes
Practical experience with Azure Data Factory, Databricks, and PySpark
Track record of designing, building, and delivering production-ready data products at enterprise scale
Strong analytical skills and ability to translate business requirements into technical solutions
Excellent communication skills in English, with the ability to adapt technical details for different audiences
Experience working in Agile/Scrum teams

Job Responsibility

Design, build, and maintain scalable, efficient, and reusable data pipelines and products on the Azure PaaS data platform
Collaborate with product owners, architects, and business stakeholders to translate requirements into technical designs and data models
Enable advanced analytics, reporting, and other data-driven use cases that support commercial initiatives and operational efficiencies
Ingest, transform, and optimize large, complex data sets while ensuring data quality, reliability, and performance
Apply DevOps practices, CI/CD pipelines, and coding best practices to ensure robust, production-ready solutions
Monitor and own the stability of delivered data products, ensuring continuous improvements and measurable business benefits
Promote a “build-once, consume-many” approach to maximize reuse and value creation across business verticals
Contribute to a culture of innovation by following best practices while exploring new ways to push the boundaries of data engineering

What we offer

Paid Vacation
Sick Days
Sport/Insurance Compensation
English Classes
Charity
Training Compensation

Senior Data Engineer

Our client is a global jewelry manufacturer undergoing a major transformation, m...

Location

Turkey , Istanbul

Salary:

Not provided

Zoolatech

Expiration Date

Until further notice

Requirements

5+ years of experience as a Data Engineer with proven expertise in Azure Synapse Analytics and SQL Server
Advanced proficiency in SQL, covering relational databases, data warehousing, dimensional modeling, and cubes
Practical experience with Azure Data Factory, Databricks, and PySpark
Track record of designing, building, and delivering production-ready data products at enterprise scale
Strong analytical skills and ability to translate business requirements into technical solutions
Excellent communication skills in English, with the ability to adapt technical details for different audiences
Experience working in Agile/Scrum teams

Job Responsibility

Design, build, and maintain scalable, efficient, and reusable data pipelines and products on the Azure PaaS data platform
Collaborate with product owners, architects, and business stakeholders to translate requirements into technical designs and data models
Enable advanced analytics, reporting, and other data-driven use cases that support commercial initiatives and operational efficiencies
Ingest, transform, and optimize large, complex data sets while ensuring data quality, reliability, and performance
Apply DevOps practices, CI/CD pipelines, and coding best practices to ensure robust, production-ready solutions
Monitor and own the stability of delivered data products, ensuring continuous improvements and measurable business benefits
Promote a “build-once, consume-many” approach to maximize reuse and value creation across business verticals
Contribute to a culture of innovation by following best practices while exploring new ways to push the boundaries of data engineering

What we offer

Paid Vacation
Hybrid Work (home/office)
Sick Days
Sport/Insurance Compensation
Holidays Day Off
English Classes
Training Compensation
Transportation compensation

Senior Data Engineer

As a Senior Data Engineer at Rearc, you'll play a pivotal role in establishing a...

Location

United States , New York

Salary:

160000.00 - 200000.00 USD / Year

Rearc

Expiration Date

Until further notice

Requirements

8+ years of professional experience in data engineering across modern cloud architectures and diverse data systems
Expertise in designing and implementing data warehouses and data lakes across modern cloud environments (e.g., AWS, Azure, or GCP), with experience in technologies such as Redshift, BigQuery, Snowflake, Delta Lake, or Iceberg
Strong Python experience for data engineering, including libraries like Pandas, PySpark, NumPy, or Dask
Hands-on experience with Spark and Databricks (highly desirable)
Experience building and orchestrating data pipelines using Airflow, Databricks, DBT, or AWS Glue
Strong SQL skills and experience with both SQL and NoSQL databases (PostgreSQL, DynamoDB, Redshift, Delta Lake, Iceberg)
Solid understanding of data architecture principles, data modeling, and best practices for scalable data systems
Experience with cloud provider services (AWS, Azure, or GCP) and comfort using command-line interfaces or SDKs as part of development workflows
Familiarity with Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, ARM/Bicep, or AWS CDK
Excellent communication skills, able to explain technical concepts to technical and non-technical stakeholders

Job Responsibility

Provide strategic data engineering leadership by shaping the vision, roadmap, and technical direction of data initiatives to align with business goals
Architect and build scalable, reliable data solutions, including complex data pipelines and distributed systems, using modern frameworks and technologies (e.g., Spark, Kafka, Kubernetes, Databricks, DBT)
Drive innovation by evaluating, proposing, and adopting new tools, patterns, and methodologies that improve data quality, performance, and efficiency
Apply deep technical expertise in ETL/ELT design, data modeling, data warehousing, and workflow optimization to ensure robust, high-quality data systems
Collaborate across teams—partner with engineering, product, analytics, and customer stakeholders to understand requirements and deliver impactful, scalable solutions
Mentor and coach junior engineers, fostering growth, knowledge-sharing, and best practices within the data engineering team
Contribute to thought leadership through knowledge-sharing, writing technical articles, speaking at meetups or conferences, or representing the team in industry conversations

What we offer

Health Benefits
Generous time away
Maternity and Paternity leave
Educational resources and reimbursements
401(k) plan with a company contribution

Fulltime