Sr. Data Engineer

Role: Data Engineer

Experience: 6-10 years

Project Duration: 6 months

Contractual Position

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

 4–8 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)

Job Type: Contractual / Temporary
Contract length: 6 months

Work Location: In person