Senior Data Engineer

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SeniorZdalnieFull-time

#480222·Dodano wczoraj·0

Źródło: Globaldev Group

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Tech Stack / Keywords

SQL Python Databricks Apache Airflow AWS Snowflake SparkDelta LakeUnity CatalogS3

Podsumowanie oferty

Build and maintain scalable data infrastructure and pipelines for a research and analytics firm creating insights from alternative data. Work with petabytes of data using Databricks, SQL, Python, Airflow, and cloud technologies.

Wymagania

3–8 years of data engineering experience.
Expert-level SQL, including complex queries, performance optimization, and window functions.
Advanced Python, including object-oriented programming, async/await, and data processing libraries.
Experience with Apache Airflow, including DAG development, custom operators, and workflow orchestration.
Experience with Databricks, including Spark optimization, Delta Lake, and Unity Catalog governance.
Experience with AWS (S3, EMR, Lambda, Glue) or an equivalent cloud platform.
Data modeling experience, including dimensional modeling, data vault, and modern data stack patterns.
Experience mentoring junior engineers and leading technical initiatives.
Strong communication skills for cross-functional collaboration.
Experience with Agile methodologies and project management.
Ability to translate business requirements into technical solutions.

Nice to have:

Experience in financial services, fintech, or data intelligence companies.
Background in consumer retail, digital media, or technology verticals.
Advanced degree in Computer Science, Statistics, Mathematics, or a related field.

Obowiązki

Design, build, and maintain scalable ETL/ELT pipelines processing petabytes of data.
Architect data solutions using AWS, Databricks, and Snowflake.
Implement real-time and batch processing workflows using Apache Airflow.
Optimize data storage and retrieval patterns for analytical workloads.
Implement data quality frameworks and monitoring systems.
Establish data governance standards and best practices.
Build automated testing and validation for data pipelines.
Develop data lineage and metadata management solutions.
Lead technical design reviews and architecture decisions.
Mentor junior data engineers and promote best practices.
Drive adoption of modern development practices, including CI/CD for data pipelines.
Use Cursor, Claude, and GitHub Copilot to accelerate development.
Implement AI-driven data quality checks and anomaly detection.
Stay current with emerging AI tools and their applications in data engineering.

Benefity

20 days of vacation.
Public holidays.

Płatne święta

Inne informacje

Working hours are 12:00–20:00 CET, with at least 2 hours of overlap with colleagues on both the US East Coast and West Coast.

Globaldev Group

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