Gypsy Collective
DWHEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“DWH Engineer at Gypsy Collective. Skills: Data Warehouse, ETL/ELT, SQL, Python. Design Data Warehouse architectures. Build Data Warehouse architectures”
What They're Looking For.
Must Have
SQL skills: complex queries, CTEs, window functions, analytical queries (5+ years experience), Knowledge of Python or other scripting languages for data transformations (4+ years experience), Deep understanding of DWH concepts: ETL/ELT, Data Vault, Kimball, Star/Snowflake schemas (5+ years experience), Experience with Airflow or other data pipeline orchestrators (5+ years experience), Hands-on experience with modern DWH and query engines: BigQuery, Snowflake, Redshift, ClickHouse, Vertica, AWS Athena, Trino (5+ years experience), Confident use of experience with team workflows (pull requests, rebasing, merge conflict resolution (5+ years experience), Understanding of server and cloud infrastructure: basic skills in configuration, maintenance, monitoring, and load control (3+ years experience)
Nice to Have
Experience with CDC tools and streaming data, Knowledge of Docker, Kubernetes, and Infrastructure as Code (Terraform), Experience with cloud platforms such as AWS, GCP, or, Familiarity with data governance, data cataloging, and lineage tools
What You'll Do.
Design Data Warehouse architectures
Build Data Warehouse architectures
Maintain Data Warehouse architectures
Develop ETL/ELT pipelines
Optimize ETL/ELT pipelines
Implement incremental loads
Implement reprocessing
Optimize query performance
Optimize pipeline performance
Integrate new data sources
Translate requirements into data solutions
Contribute to data engineering standards
How You'll Work.
Team & Collaboration
Collaborate with analysts; Collaborate with developers; Collaborate with business stakeholders; Collaborate with engineers; Collaborate with BI teams
Full Job Description
Gypsy Collective is looking for a **DWH Engineer** to join our team and help build scalable, reliable, and high-performance data warehouse solutions that support analytics and business decision-making. We are looking for an experienced and proactive engineer who can work across the full data lifecycle - from ingestion and modeling to optimization, monitoring, and automation - while collaborating closely with analysts, developers, and business stakeholders. **📅 Your daily adventures include: ** * Designing, building, and maintaining scalable Data Warehouse architectures aligned with business needs; * Developing and optimizing ETL/ELT pipelines using Python, Airflow, and custom solutions; * Working with DWH/Data Lake technologies including PostgreSQL, Trino, and BigQuery; * Implementing incremental loads, CDC, backfills, and reprocessing strategies; * Optimizing query performance, data models, and pipeline execution; * Ensuring data quality through validation, automated testing, monitoring, and alerting; * Integrating new data sources (APIs, third-party systems, raw data) without disrupting existing pipelines; * Collaborating with analysts, engineers, BI teams, and business stakeholders to translate requirements into scalable data solutions; * Reviewing code, mentoring engineers, and contributing to data engineering standards and best practices. **Requirements** **🧭 What makes you a great match: ** * Strong SQL skills: complex queries, CTEs, window functions, analytical queries (5+ years experience); * Knowledge of Python or other scripting languages for data transformations (4+ years experience); * Deep understanding of DWH concepts: ETL/ELT, Data Vault, Kimball, Star/Snowflake schemas (5+ years experience); * Experience with Airflow or other data pipeline orchestrators (5+ years experience); * Hands-on experience with modern DWH and query engines: BigQuery, Snowflake, Redshift, ClickHouse, Vertica, AWS Athena, Trino (5+ years experience); * Confident use of Git; e
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