Description

You will own data pipeline reliability, customer onboarding, and data quality for our platform.

This role is remote.

Responsibilities

• Monitor automated batch and streaming data pipelines in AWS, troubleshooting failures and resolving data processing issues.
• Investigate file errors, schema mismatches, and transformation problems; perform root cause analysis and document resolutions.
• Collaborate with customers to define file formats and data structures, creating mapping templates for ingestion.
• Write SQL queries to validate data accuracy and develop Python scripts for data validation and automation checks.
• Partner with internal teams to enhance platform scalability, resilience, and observability.

Required Skills

• 6–10 years of experience in data operations or data engineering roles.
• Hands-on experience with AWS services, including S3, Glue, Lambda, CloudWatch, and Redshift.
• Strong SQL skills for joins, aggregation, and troubleshooting data discrepancies.
• Working knowledge of Python for scripting and data validation tasks.
• Experience with ETL/ELT orchestration tools.
• Familiarity with structured and semi-structured data formats (CSV, JSON, Parquet).
• Experience troubleshooting automated data pipelines.

Preferred Skills

• Experience working within a data lake or data warehouse architecture.
• Familiarity with data catalogs or governance frameworks.

Key Skills

Education

Any Gradute