GENERAL FUNCTION

We are hiring a Lead Data Engineer to design and deliver scalable data pipelines and data solutions on our modern data stack, centered on Snowflake on AWS, Snowflake Openflow (Apache NiFi), dbt, PostgreSQL, Python, and SQL. This is a senior hands-on engineering role responsible for translating business and data requirements into sound technical designs, building and optimizing pipelines, and delivering reliable data products. The role leads Data Operations support and serves as a senior coordination point for India-based data colleagues, helping organize priorities, remove blockers, and maintain continuity across the broader Data team while working within established reporting lines. A key focus is maturing Data Operations through automated monitoring and proactive support.

DUTIES/RESPONSIBILITIES

Data engineering, solution design, and delivery

Lead the end-to-end design and delivery of scalable data pipelines and data solutions using Snowflake, Snowflake Openflow (Apache NiFi), and dbt.
Translate business and data requirements into technical designs, data flows, integration patterns, data models, and delivery plans.
Build and maintain ingestion and orchestration flows in Openflow, transformation models in dbt, and performant data structures and workloads in Snowflake.
Design reusable patterns for batch, change data capture, API, and file-based ingestion, including validation, reconciliation, restartability, and recovery.
Develop in advanced SQL and Python and remain hands-on through code reviews, troubleshooting, performance tuning, and resolution of complex engineering issues.
Ensure solutions meet expectations for data quality, security, scalability, maintainability, observability, and cost efficiency.
Collaborate with architecture, analytics, platform, security, application, and business teams to align designs, data contracts, dependencies, and delivery outcomes.
Maintain clear technical documentation and contribute reusable engineering patterns and standards across the broader Data team.

Data Operations leadership and team coordination

Lead Data Operations support and coordinate priorities, handoffs, and issue resolution across India-based data colleagues, working within established reporting lines.
Establish and reinforce engineering practices for source control, peer review, testing, CI/CD, deployment, documentation, and production readiness.
Mentor colleagues through design and code reviews, promote cross-training, and help engineers independently deliver and support data solutions.
Own and mature Data Operations, including support coverage, incident response, escalation paths, runbooks, recovery procedures, and service expectations.
Drive automated monitoring, alerting, and recovery across Snowflake, Openflow, dbt, databases, and pipeline workloads to reduce manual checks and identify issues proactively.
Track service health and incident trends, lead root-cause analysis, and maintain a prioritized plan to improve reliability and operational efficiency.

EXPERIENCE & EDUCATION

Bachelor's degree in computer science, engineering, information systems, or an equivalent combination of education and relevant experience.
10+ years of hands-on data engineering experience, including at least 2 years leading technical delivery or production operations.
Strong production experience with Cloud data technologies in one of Snowflake, AWS, Azure or GCP including solution design, data structures, performance tuning, workload management, security, and cost optimization.
Strong hands-on experience with dbt, including model design, testing, documentation, dependencies, reusable macros, and deployment across environments.
Experience with Git-based development, automated testing, CI/CD, Terraform, and repeatable environment-promotion practices.
Advanced SQL skills with experience and a track record of building maintainable, testable production data pipelines and data products.
Experience designing ETL/ELT solutions across batch, CDC, API, and file-based ingestion and applying sound data modeling, quality, validation, and recovery practices.