Senior Data Engineer

About the Role

We are building a modern, scalable data platform to support complex operational, financial, and compliance reporting across the organization. As a Senior / Lead Data Engineer, you will play a critical role in designing and building the foundational systems that power this platform.

You will work on data pipelines and storage systems that process billions of records, integrate diverse internal and external data sources, and uphold high standards of data availability, reliability, and quality. Your responsibilities will span the full data lifecycle from ingesting raw data to modeling and delivering structured, query-optimized datasets used for analytics, reporting, and downstream applications.

In this role, you will also act as a technical lead and single point of contact for data engineering initiatives. You will bring strong ownership and accountability, drive work end-to-end, and communicate clearly with engineering, analytics, product, and business stakeholders to ensure successful delivery of the data platform.

Requirements

• 5–10 years of experience in data engineering or backend-heavy engineering roles
• Strong proficiency in Groovy, Python, or similar scripting languages
• Deep expertise in building robust ETL/ELT pipelines and analytical warehouse models
• Hands-on experience with OLAP databases such as ClickHouse, Redshift or SnowFlake
• Experience integrating with object storage systems like Amazon S3 and MinIO
• Hands-on experience with modern data engineering tools such as Apache Spark, Airflow, SQL-based analytics engines, and data ingestion/orchestration tools (e.g., Apache NiFi).
• Proven ability to lead initiatives, take end-to-end ownership, and act as a single point of contact
• Strong communication skills with the ability to work effectively across technical and non-technical teams
• Comfort operating in fast-paced, high-ownership environments

Responsibilities

• Lead the design and evolution of the core data platform, including pipelines and warehouse layers
• Act as the primary point of contact for data engineering workstreams
• Drive end-to-end ownership of delivery, from requirements to production readiness
• Design, model, and maintain structured datasets for reporting and analytics
• Develop and maintain ETL pipelines for raw ingestion and analytics-ready tables
• Write and optimize complex, high-scale queries processing billions of records
• Perform data exploration to identify quality issues, inconsistencies, and optimization opportunities
• Implement transformation and automation logic using Groovy or Python
• Manage data infrastructure across on-prem and AWS environments
• Collaborate closely with engineers, analysts, product, and business teams
• Define and enforce data validation, audit, and alerting mechanisms
• Provide technical guidance and raise the overall bar for data engineering practices

The Ideal Candidate

You are a hands-on leader with strong data instincts. You take ownership naturally, hold yourself and others accountable, and communicate clearly and proactively. You enjoy building systems, understanding data deeply, and connecting the dots across complex data flows. You thrive in environments where leadership, pragmatism, and execution matter more than titles.