Senior Data Engineer

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We are seeking a skilled and detail-oriented Senior Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. You will be responsible for transforming raw data into reliable, high-quality datasets that fuel analytics, reporting, and machine learning initiatives. The ideal candidate is passionate about data quality, automation, and solving complex data challenges in a collaborative environment.

Key Responsibilities:

Design & Build Pipelines: Develop, deploy, and monitor robust, scalable, and efficient ETL/ELT data pipelines using modern tools and frameworks.

Data Modeling & Architecture: Design, implement, and optimize data models (relational, dimensional, NoSQL) in data warehouses, data lakes, or lakehouses.

Data Integration: Ingest, process, and integrate data from diverse sources (Kafka, pub-sub, databases, APIs, streaming platforms, SaaS applications, flat files).

Data Quality & Governance: Implement data validation, cleansing, and monitoring processes to ensure accuracy, consistency, and reliability of data assets.

Infrastructure & Optimization: Manage and optimize cloud data infrastructure (e.g., GCP, AWS, Azure) and on-premise systems for performance, cost-efficiency, and scalability.

Collaboration: Partner closely with Data Analysts, Data Scientists, and business stakeholders to understand data requirements and deliver solutions that meet their needs.

Automation & CI/CD: Automate data pipeline deployments, testing, and monitoring using CI/CD principles and tools.

Documentation: Maintain clear and comprehensive documentation for data pipelines, models, and processes.

Troubleshooting: Investigate and resolve data pipeline failures, performance bottlenecks, and data quality issues.

On-call Support: This role requires to be available for out-of-office on-call support on a rotation.

Required Qualifications:

Experience: 7+ years of professional experience in data engineering or a related role across GCP services

SQL: Strong expertise in writing complex, optimized SQL queries for data extraction and transformation.

ETL/ELT: Hands-on experience building data pipelines using frameworks like Apache Spark, Apache Airflow, DBT, Fivetran, Matillion, or equivalent.

Databases: Solid understanding of relational databases (e.g., PostgreSQL, MySQL) and experience with modern data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Synapse).

Data Modeling: Knowledge of data modeling principles (e.g., star schema, snowflake schema, normalization).

Programming: Proficiency in Python and/or Scala for data processing and pipeline development.

Agentic workflows: Experience using agentic workflows in day-to-day deliveries

Version Control: Experience with Git and collaborative development workflows.

Problem-Solving: Strong analytical and problem-solving skills with a focus on data quality and system reliability.

Communication: Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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