
Sr. Data Engineer
3 weeks ago
About the Role
Were building a modern data platform designed to support complex reporting and analytics across the organization — including operational, financial, and compliance use cases. As a Senior / Lead Data Engineer (Platform Focus), you'll work on the foundational systems that enable this platform: processing billions of records, integrating diverse data sources, and ensuring the availability, reliability, and usability of data.
Within this platform, you'll also contribute to the ETL pipelines and warehouse models that power critical reports and analytics. Your role will span from ingesting raw data to shaping structured, queryable datasets used for decision-making.
The Ideal Candidate
You're a generalist with strong data instincts. You care about correctness, performance, and maintainability. You enjoy building systems, understanding data deeply, and connecting the dots across complex data flows. You're comfortable wearing multiple hats in a fast-moving environment where platform thinking and pragmatism go hand in hand.
Responsibilities
- Help build and evolve the core data platform, including pipelines and data warehouse layers
- Design and maintain structured datasets to support reporting and analytics
- Work with structured and semi-structured data across PostgreSQL, MySQL, and MongoDB
- Develop and maintain ETL pipelines for both raw data and analytics-ready warehouse tables
- Write and optimize complex queries to process billions of records efficiently
- Perform data exploration and mining to uncover patterns, inconsistencies, or optimization opportunities
- Write transformation and automation logic using Groovy or Python
- Manage infrastructure across on-prem and AWS environments
- Collaborate with engineers, analysts, and product teams to solve business problems with data
- Define and enforce data validation, audit, and alerting mechanisms
Requirements
- 4–7 years of experience in data engineering or a related backend/data-heavy role
- Strong SQL skills and deep understanding of query performance tuning
- Proficient in Groovy or Python for scripting and automation
- Hands-on experience with PostgreSQL, MySQL, and MongoDB at scale
- Experience working with or building for a data warehouse (e.g., Redshift, Trino, PostgreSQL)
- Comfortable working in cloud (AWS) and/or on-prem environments
- Experience building and operating production data systems and pipelines
- Strong problem-solving skills and a bias toward ownership and action
- Ability to debug across systems and connect the dots in complex data flows
Nice to Have
- Experience with Apache NiFi, Airflow, or custom orchestrators
- Exposure to data mining, anomaly detection, or pattern recognition techniques
- Familiarity with warehouse modeling concepts (fact/dim tables, reporting views)
- Experience with tools like Trino, AWS Athena, Metabase, or similar query/BI platforms
- Familiarity with observability practices (monitoring, alerting, logging)
- Exposure to streaming systems (Kafka, Spark, Flink)
- Experience supporting compliance or finance-focused data workflows
- Comfort working in containerized setups (Docker/Kubernetes)
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