Sr. Data Engineer
Posted on August 21, 2025
Job Description
- Sr. Data Engineer
- Location: Remote
- As a Senior Data Engineer, you will be responsible for designing, developing, and maintaining
- scalable data pipelines that process multi-client advertising and sales data. You will be part of a
- high-powered engineering team building next-generation marketing analytics infrastructure.
- Your primary focus will be creating reliable, multi-tenant data processing systems that handle
- 50+ enterprise clients, processing large files efficiently while maintaining data quality and
- system reliability. This role requires expertise in building production-grade ETL pipelines that
- never break, scale seamlessly, and handle complex multi-client data architectures.
- Key Responsibilities -
- ? Design and build scalable, multi-tenant data pipelines on AWS (e.g. Glue, Step
- Functions,ECS-fargate,etc) to ingest, validate, and transform high-volume datasets from
- our third-party data hub using incremental ETL techniques
- ? Implement robust error handling and monitoring with automated recovery
- mechanisms, ensuring 3 9s of pipeline uptime
- ? Design flexible data schemas that accommodate varying client data structures and
- evolving business requirements
- ? Create automated data validation systems with client-specific business rules and
- quality thresholds.
- ? Implement comprehensive data quality monitoring with automated anomaly detection
- and alerting systems.
- ? Design pipelines that can be safely re-run, handle backfills/late data, and produce
- consistent results every time.
- ? Focus on writing well-tested, well-documented code with appropriate unit tests and
- automated integration tests.
- ? Define and enforce data contracts & schema versioning (e.g. Glue Catalog/registry),
- including safe schema evolution and compatibility rules across clients.
- ? Contribute to CI/CD implementation for data pipelines with automated testing and
- deployment
- ? Collaborate with MLOps Engineers, Product Management, and business stakeholders to
- deliver data solutions that enable marketing insights.
- Required Skills
- ? 7+ years of data engineering experience with a proven track record of delivering
- enterprise-grade data solutions and high-volume ETL pipelines.
- ? Expert-level Python (5+ years) and advanced SQL expertise with deep knowledge of
- data processing libraries (Pandas, PySpark) and performance optimization for large-
- scale datasets
- ? AWS data services expertise (4+ years) including Glue, S3, Athena, Step Functions,
- and experience designing data lake architectures for enterprise applications
- ? Multi-tenant system experience with proven ability to build scalable data processing
- systems that handle multiple enterprise clients securely and efficiently
- ? Large-scale data processing experience with GB+ files, incremental processing
- strategies, and production debugging skills for distributed data systems
- ? Data quality and CI/CD including validation frameworks, monitoring systems,
- automated testing, and deployment strategies.
- ? Security & governance: secure-by-default data lake with least-privilege access,
- encryption, private network access, and auditable activity.
- Qualifications
- ? Bachelors or Master's degree in Computer Science, Computer Engineering, or related
- technical field
- ? 7+ years of professional software engineering experience with focus on data systems
- ? Proven track record of building and maintaining production data pipelines serving
- enterprise clients
- ? Portfolio of successful projects demonstrating scalable data architecture and multi-
- client system design.
Required Skills
? 7+ years of data engineering experience with a proven track record of delivering enterprise-grade data solutions and high-volume etl pipelines. ? expert-level python (5+ years) and advanced sql expertise with deep knowledge of data processing libraries (pandas
pyspark) and performance optimization for large- scale datasets ? aws data services expertise (4+ years) including glue
s3
athena
step functions
and experience designing data lake architectures for enterprise applications ? multi-tenant system experience with proven ability to build scalable data processing systems that handle multiple enterprise clients securely and efficiently ? large-scale data processing experience with gb+ files
incremental processing strategies
and production debugging skills for distributed data systems ? data quality and ci/cd including validation frameworks
monitoring systems
automated testing
and deployment strategies. ? security & governance: secure-by-default data lake with least-privilege access
encryption
private network access
and auditable activity.