Gypsy Collective
MiddleDWHEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Middle DWH Engineer at Gypsy Collective. Skills: Data warehousing, Data Lake, ETL/ELT, Data pipelines. Design DWH solutions. Build DWH solutions”
Industry & Context.
Troubleshoot; Optimize
What They're Looking For.
Must Have
3+ years SQL, 3+ years data ingestion processes, 3+ years Apache Airflow, 2+ years Python, 3+ years DWH concepts, 3+ years production data pipelines, PostgreSQL and Trino experience, modern analytical databases experience, Git and collaborative development workflows
Nice to Have
Change Data Capture (CDC) tools experience, incremental loading experience, AWS, GCP, or Azure experience, Docker and containerized experience, streaming or near real-time data pipelines experience, dbt or similar data transformation experience, data cataloging, lineage, or governance tools experience
What You'll Do.
Maintain DWH solutions
Design Data Lake solutions
Build Data Lake solutions
Maintain Data Lake solutions
Optimize ETL pipelines
Support ETL pipelines
Optimize ELT pipelines
Support ELT pipelines
Integrate data flows from APIs
Integrate data flows from databases
Integrate data flows from SaaS platforms
Integrate data flows from third-party
Maintain data flows from APIs
Maintain data flows from databases
Maintain data flows from SaaS platforms
Maintain data flows from third-party
Implement incremental loading
Implement CDC processes
Implement reprocessing
Monitor data pipelines
Troubleshoot data pipelines
Improve data pipelines
Implement data quality checks
Implement validation rules
Implement automated monitoring
Collaborate with analysts
Collaborate with BI developers
Collaborate with engineers
Collaborate with business stakeholders
Deliver scalable data
Participate in code reviews
Contribute to engineering standards
Contribute to best practices
How You'll Work.
Team & Collaboration
Analysts; BI developers; Engineers; Business stakeholders
Full Job Description
We are looking for a **Middle DWH Engineer** to design, build, and maintain scalable data warehouse solutions that support analytics and business decision-making. You will work across the full data lifecycle - from data ingestion and transformation to orchestration and optimization - while collaborating with analysts, engineers, and business stakeholders. **📅 Your adventures include:** * design, develop, and maintain DWH and Data Lake solutions aligned with business requirements; * build, optimize, and support ETL/ELT pipelines using Python, SQL, Airflow, and related technologies; * integrate and maintain data flows from APIs, databases, SaaS platforms, and third-party systems; * work with PostgreSQL, Trino, and cloud-based analytical platforms to support reporting and analytics needs; * implement and support incremental loading, CDC processes, backfills, and reprocessing workflows; * monitor, troubleshoot, and improve data pipelines to ensure reliability, stability, and timely delivery of data; * implement data quality checks, validation rules, and automated monitoring processes; * optimize SQL queries, data models, and pipeline performance; * collaborate with analysts, BI developers, engineers, and business stakeholders to deliver scalable data solutions; * participate in code reviews and contribute to engineering standards and best practices. **Requirements** **🧭 What makes you a great match:** * strong SQL skills, including complex queries, CTEs, window functions, analytical queries, and query optimization (3+ years); * strong experience integrating external data sources, including REST APIs, databases, SaaS platforms, and third-party systems; ability to design, develop, troubleshoot, and maintain reliable data ingestion processes in production environments (3+ years); * experience with Apache Airflow or similar workflow orchestration tools (3+ years); * experience with Python for data processing, integrations, and automation (2+ years); * good understanding o
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