Build, optimize, and maintain production data pipelines using SQL, dbt, Python, and PySpark. Own data quality testing, workflow monitoring, alert management, failure debugging, schema drift handling, and CI/CD deployment. Transform large-scale datasets in a Databricks Lakehouse environment while ensuring reliable performance and data integrity. Clearly communicate technical issues, root causes, resolutions, and action plans to technical teams and business stakeholders.
About V4C
At V4C, we empower enterprise organizations to unlock the full value of their data. As a fast-growing technology consultancy, our Databricks practice partners with industry leaders to architect modern data platforms, build high-performance data pipelines, and accelerate enterprise AI and analytics initiatives.
We are seeking a production-focused Senior Data Engineer with exceptional communication skills and a proven track record of delivering reliable data pipelines. In this role, you will have end-to-end production ownership of our data platforms, ensuring high data quality and robust system performance. The ideal candidate prioritizes practical problem-solving and hands-on execution over high-level architecture. You excel at debugging complex data issues and can clearly
communicate technical resolutions using a direct, impact-driven approach.
Key Responsibilities
- Pipeline Development: Build, optimize, and maintain robust data pipelines using SQL, dbt, and Python.
- Data Quality & Testing: Implement rigorous data-quality checks and automated testing frameworks within dbt to proactively catch anomalies.
- Production Ownership: Monitor production workflows, manage alerts, and rapidly debug pipeline failures from root cause to permanent fix.
- Data Transformation: Write efficient PySpark transformations to process large-scale datasets within our Lakehouse environment.
- Collaboration & Communication: Translate complex data issues into clear, concise action plans for both technical teammates and business stakeholders.
Required Skills & Experience
Core Technical Expertise
- SQL & dbt: Expert-level SQL skills and extensive hands-on experience building modular models, snapshots, and custom schema tests in dbt.
- Python: Strong proficiency in writing clean, maintainable Python scripts for data manipulation, automation, and API integrations.
- PySpark: Decent, practical experience utilizing PySpark for data transformation and basic performance tuning (e.g., handling joins, DataFrame API).
- Lakehouse Knowledge: Functional understanding of Delta Lake or similar Lakehouse technologies, including ACID transactions and MERGE operations.
Execution & Soft Skills
- Strong Communication: Exceptional written and spoken communication skills. Ability to explain problems and results directly and concisely.
- Debugging & Problem Solving: Superior troubleshooting skills with a methodical approach to identifying root causes and validating fixes.
- Production Mindset: Experience owning pipelines end-to-end, including CI/CD deployment, monitoring, and handling schema drift.
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