Senior Data Engineer
Summary
Build and optimize scalable ETL pipelines, real-time data ingestion, and multi-tenant analytical databases to power sub-second BI dashboards and embedded analytics for a media-focused SaaS platform.
- Design and build scalable ETL pipelines to move data from transactional systems into analytical data warehouses
- Develop real-time and batch data ingestion systems for social media, campaign, and user metrics
- Create multi-tenant data models with strong data isolation and partitioning strategies
- Build and optimize analytical databases for high performance and low-latency queries (sub-second dashboards)
- Implement data quality checks, validation frameworks, monitoring, and alerting
- Design and maintain secure data access using Row-Level Security (RLS) and Role-Based Access Control (RBAC)
- Build authentication and session-based access control for multi-tenant environments
- Develop optimized SQL transformations for BI dashboards and embedded analytics
- Create aggregated tables, materialized views, and denormalized datasets for reporting
- Work with ETL orchestration tools like Apache Airflow, Prefect, or dbt
- Optimize OLAP systems using partitioning, indexing, compression, and query tuning
- Support high-concurrency analytics workloads with large-scale datasets
- Collaborate on BI and analytics integrations for internal teams and enterprise clients
- Ensure compliance with security standards like SOC2 and GDPR
Technologies used:
- SQL (expert level)
- Python (pandas, numpy, pyarrow)
- ETL tools: Apache Airflow, Prefect, dbt
- Analytical databases: ClickHouse, BigQuery, Snowflake, Redshift
- Streaming systems: Apache Kafka, Pulsar, Kinesis
- OLAP / data warehouse optimization techniques
- BI / embedded analytics platforms
- Data modeling, semantic layers, and metrics systems
- 5+ years of experience in Data Engineering in production-scale environments
- Very strong SQL skills and experience with analytical / columnar databases
- Strong Python skills, especially for data processing (pandas, numpy, pyarrow)
- Experience building ETL pipelines and data orchestration workflows (Airflow, Prefect, dbt)
- Solid understanding of OLAP systems, data warehousing, and performance optimization
- Experience with multi-tenant SaaS data platforms and data isolation concepts
- Knowledge of Row-Level Security (RLS), RBAC, and secure data access patterns
- Experience with distributed or streaming systems (Kafka, Pulsar, or Kinesis) is a plus
- Familiarity with BI tools, embedded analytics, and dashboarding systems
- Understanding of data compliance requirements (SOC2, GDPR)
- Experience with scalable, real-time data processing systems is a strong advantage
- People: work with talented, collaborative, and friendly people who love what they do.
- Guidance: utilize our learning platform to fully get the training and tools you'll need to become successful here from your first day with us.
- Surprise meal stipends: work from home can't stop the enjoyment of someone else making a meal for you!
- Work/life harmony: 26 days vacation, floating and set holidays, wellness allowance, and paid parental leave.
- Medical insurance, life insurance, and business travel insurance
- Stock options as part of our equity-sharing program.
- Comprehensive perks program providing stipends for cell phone and internet, home office setup, mental wellness, professional development and tuition reimbursement, plus occasional company-funded meal opportunities throughout the year.