Senior Data Engineer (Serbia)
Novi Sad, Serbia
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s listing: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s listing: Full-Time
From the employer’s posting
What you’ll work on
Full postingDrive end-to-end data platform projects from requirements to production hand-over
Build and optimize batch, micro-batch and real-time ETL/ELT pipelines
Automate data stack deployment via Git-based CI/CD, observability and cost controls
Implement data governance controls including GDPR-compliant PII handling and quality tests
Mentor mid-level engineers and contribute to architecture standards and run books
From the employer’s posting
Drive end-to-end data‐platform projects, from requirement workshops to production hand-over
Build and optimize ETL/ELT pipelines (batch, micro-batch, and true real-time)
Automate deployment of data stacks via Git-based CI/CD, observability, and cost-controls at every stage.
Implement data-governance controls (GDPR-compliant PII handling, lineage, quality tests)
Mentor mid-level engineers, codify best practices, and contribute to architecture standards and run books.
Tools in this posting
- Python
- SQL
- AWS
- Azure
- Databricks
- dbt
- Delta Lake
- GCP
- Grafana
- Kafka
- Snowflake
- Spark
- Terraform
- Airflow
- PySpark
Source — Tool mentions in context
- Drive end-to-end data‐platform projects, from requirement workshops to production hand-over, using Databricks, Microsoft Fabric, Snowflake, and associated cloud services. - Build and optimize ETL/ELT pipelines (batch, micro-batch, and true real-time) with Python/PySpark, dbt, Airflow, Kafka/Flink, and cloud-native tools. - Automate deployment of data stacks via Git-based CI/CD, observability, and cost-controls at every stage.
- Proven track record building both batch and streaming pipelines. - Strong Python and SQL. - Solid grasp of CI/CD (GitHub Actions, Azure DevOps, or similar) and Infrastructure-as-Code (Terraform or CloudFormation).
We’re expanding our Data Engineering practice and looking for a senior-level engineer who can design, automate, and scale modern lakehouse and warehouse platforms on Azure, AWS, or GCP. In this role, you’ll not only partner with product managers, analysts, and data scientists to unlock governed, high-quality data for batch and streaming use-cases, but also lead internal initiatives for driving proof-of-concepts, involved in pre-sales activities, building reusable frameworks, and setting reference architectures that raise the bar for the entire team. You’ll steward our engineering standards and turn innovative ideas into production-ready solutions that accelerate both client projects and our own platform evolution. What you’ll do:
What we’re looking for: - 5+ years in data engineering, with at least 3 years in a cloud environment (AWS, Azure, or GCP). - Expert knowledge of data-warehouse modeling concepts (star/snowflake, Data Vault, lakehouse).
- Strong Python and SQL. - Solid grasp of CI/CD (GitHub Actions, Azure DevOps, or similar) and Infrastructure-as-Code (Terraform or CloudFormation). - Familiarity with DataOps, observability (Great Expectations, Monte Carlo, Prometheus/Grafana), and security best practices.
What you’ll do: - Drive end-to-end data‐platform projects, from requirement workshops to production hand-over, using Databricks, Microsoft Fabric, Snowflake, and associated cloud services. - Build and optimize ETL/ELT pipelines (batch, micro-batch, and true real-time) with Python/PySpark, dbt, Airflow, Kafka/Flink, and cloud-native tools.
- Expert knowledge of data-warehouse modeling concepts (star/snowflake, Data Vault, lakehouse). - Hands-on experience with Databricks (Spark/Delta Live Tables), Microsoft Fabric (OneLake, Data Pipelines), or Snowflake, including performance tuning and cost optimization. - Proven track record building both batch and streaming pipelines.
- Experience designing data pipelines that power GenAI solutions - Certifications in any major cloud or Databricks/Snowflake platforms. We appreciate the interest of all applicants. Please note that only those whose qualifications align closely with the position requirements will be contacted for the next steps in the selection process.
- Solid grasp of CI/CD (GitHub Actions, Azure DevOps, or similar) and Infrastructure-as-Code (Terraform or CloudFormation). - Familiarity with DataOps, observability (Great Expectations, Monte Carlo, Prometheus/Grafana), and security best practices. Nice to have:
Posting record
Report an errorOpen 4 monthsWe first saw this listing 140 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 4, 2026 · 140 days ago
- Recorded sightings
- 81
- Last seen by us
- Oct 22, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
We’re expanding our Data Engineering practice and looking for a senior-level engineer who can design, automate, and scale modern lakehouse and warehouse platforms on Azure, AWS, or GCP. In this role, you’ll not only partner with product managers, analysts, and data scientists to unlock governed, high-quality data for batch and streaming use-cases, but also lead internal initiatives for driving proof-of-concepts, involved in pre-sales activities, building reusable frameworks, and setting reference architectures that raise the bar for the entire team. You’ll steward our engineering standards and turn innovative ideas into production-ready solutions that accelerate both client projects and our own platform evolution.
What you’ll do:
- Drive end-to-end data‐platform projects, from requirement workshops to production hand-over, using Databricks, Microsoft Fabric, Snowflake, and associated cloud services.
- Build and optimize ETL/ELT pipelines (batch, micro-batch, and true real-time) with Python/PySpark, dbt, Airflow, Kafka/Flink, and cloud-native tools.
- Automate deployment of data stacks via Git-based CI/CD, observability, and cost-controls at every stage.
- Implement data-governance controls (GDPR-compliant PII handling, lineage, quality tests) using Unity Catalog, Purview, or Fabric’s governance layer.
- Mentor mid-level engineers, codify best practices, and contribute to architecture standards and run books.
- Troubleshoot production workloads, continually improve performance, document models, dictionaries, and run books for stakeholders.
What we’re looking for:
- 5+ years in data engineering, with at least 3 years in a cloud environment (AWS, Azure, or GCP).
- Expert knowledge of data-warehouse modeling concepts (star/snowflake, Data Vault, lakehouse).
- Hands-on experience with Databricks (Spark/Delta Live Tables), Microsoft Fabric (OneLake, Data Pipelines), or Snowflake, including performance tuning and cost optimization.
- Proven track record building both batch and streaming pipelines.
- Strong Python and SQL.
- Solid grasp of CI/CD (GitHub Actions, Azure DevOps, or similar) and Infrastructure-as-Code (Terraform or CloudFormation).
- Familiarity with DataOps, observability (Great Expectations, Monte Carlo, Prometheus/Grafana), and security best practices.
Nice to have:
- Experience designing data pipelines that power GenAI solutions
- Certifications in any major cloud or Databricks/Snowflake platforms.
We appreciate the interest of all applicants. Please note that only those whose qualifications align closely with the position requirements will be contacted for the next steps in the selection process.
All applications will be handled with confidentiality.
Source details
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- Location & working pattern
Novi Sad, Serbia
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