DATA ENGINEER

The Data Engineer will be responsible for building reliable data pipelines, integrating multiple data sources, and ensuring high-quality, accessible, and well-structured data for analytics and product teams. The role works closely with Product, Analytics, Engineering, and Cloud teams to enable data-driven decision-making.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Integrate data from multiple sources, including APIs, databases, and third-party systems.
• Develop and optimize data models for analytics and reporting use cases.
• Ensure data quality, integrity, and consistency across systems.
• Support real-time and batch data processing workflows.
• Collaborate with Product and Analytics teams to define data requirements.
• Monitor and troubleshoot data pipeline performance and failures.
• Implement data governance, security, and access controls.
• Support BI and analytics teams with clean and structured datasets.
• Continuously improve data architecture, performance, and scalability.

Required Qualifications

• 6-8 years of experience in data engineering or related roles.
• Strong understanding of data structures, databases, and data modeling.
• Experience building ETL/ELT pipelines in production environments.
• Good problem-solving and analytical skills.
• Experience working in Agile and cross-functional teams.
• Strong communication and documentation abilities.

Technical Skills

• Programming:
  Python, SQL (advanced level)
• Data Processing:
  Spark, Kafka, or similar distributed systems (preferred)
• Databases:
  PostgreSQL, MySQL, MongoDB, or equivalent
• Data Warehousing:
  Snowflake, Big Query, Redshift (preferred)
• ETL/ELT Tools:
  Airflow, dbt, or similar
• BI Tools:
  Tableau, Power BI, or similar (supporting role) Tableau