Data Engineer

Job Responsibilities:

• Design and build scalable batch and streaming data pipelines.
• Develop and optimize ETL/ELT workflows using distributed data processing frameworks.
• Own and optimize ClickHouse clusters for large-scale analytical workloads.
• Design efficient data models for reporting and dashboarding use cases.
• Build and maintain data ingestion pipelines from MongoDB, PostgreSQL, Kafka, APIs, and other data sources.
• Improve performance of large SQL workloads and analytical queries.
• Build reliable monitoring, health checks, and data anomaly detection systems.
• Work closely with Product, Analytics, and Backend teams to deliver reliable reporting and insights. 

Basic Qualifications:

• 3+ years of experience in Data Engineering.
• Strong SQL skills with expertise in query optimization.
• Experience with ClickHouse or other OLAP databases (BigQuery, Redshift, Snowflake, Druid, Pinot, etc.).
• Strong knowledge of PostgreSQL.
• Experience building ETL/ELT pipelines.
• Proficiency in Java or Python.
• Experience with Apache Kafka and event-driven architectures.
• Strong understanding of data modeling and partitioning strategies.
• Experience working on cloud platforms (AWS/GCP/Azure).
• Experience with Docker and Kubernetes.
• Knowledge of monitoring and observability tools. 

Preferred Qualifications:

• Experience with Looker or BI platforms.
• Experience with Apache Spark or Dataproc.
• Experience with Airflow or workflow orchestration tools.
• Understanding of advertising technology (DSP, RTB, Attribution, Campaign Reporting).
• Experience with large-scale analytical systems processing billions of records.