Data Engineer
Indexed description
At ShyftLabs, we live and breathe data. Since 2020, we’ve been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact. We’re growing fast and we’re looking for passionate problem-solvers who are ready to turn big ideas into real outcomes.
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.
- 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.
- 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.
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