Lead Data Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Create and implement scalable data pipelines and solutions utilizing Snowflake, Snowflake Openflow (Apache NiFi), and dbt.

• Convert business and data requirements into technical designs, data flows, integration patterns, data models, and delivery strategies.

• Develop and sustain ingestion and orchestration flows in Openflow, dbt transformation models, and efficient Snowflake workloads.

• Design reusable patterns for batch, change-data-capture, API, and file-based ingestion that incorporate validation, reconciliation, restartability, and recovery.

• Create advanced SQL and Python solutions through code reviews, troubleshooting, performance optimization, and resolution of complex issues.

• Ensure that data solutions fulfill expectations concerning data quality, security, scalability, maintainability, observability, and cost-efficiency.

• Collaborate effectively with architecture, analytics, platform, security, application, and business teams.

• Maintain technical documentation along with reusable engineering patterns and standards.

• Lead Data Operations support, coordinating priorities, handoffs, and issue resolution with data colleagues based in India.

• Establish best practices for engineering, including source control, peer review, testing, CI/CD, deployment, documentation, and production readiness.

• Mentor peers through design and code reviews while encouraging cross-training.

• Oversee and enhance Data Operations, including support coverage, incident response, escalation procedures, runbooks, recovery processes, and service expectations.

• Drive automation in monitoring, alerting, and recovery across data platforms and pipeline workloads.

• Monitor service health and incident trends, lead root-cause analysis, and enhance reliability and operational efficiency.

⛳️ Requirements

• Bachelor’s degree in computer science, engineering, information systems, or a comparable mix of education and relevant experience.

• Over 10 years of practical data engineering experience, including at least 2 years in leading technical delivery or production operations.

• Robust production experience with cloud data technologies such as Snowflake, AWS, Azure, or GCP.

• Proficiency in solution design, data structures, performance tuning, workload management, security, and cost optimization.

• Extensive hands-on experience with dbt, covering 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 capabilities and experience in building maintainable, testable production data pipelines and data products.

• Experience in designing ETL/ELT solutions across batch, CDC, API, and file-based ingestion.

• Familiarity with data modeling, quality, validation, and recovery practices.

• Strong skills in solution design, communication, and technical leadership.

• Ability to influence decisions, mentor engineers, and collaborate across business and technology teams.

• Nice to have: Experience with Snowflake and AWS in production settings.

• Nice to have: Experience with Apache NiFi or Snowflake Openflow.

• Nice to have: Experience with relational databases such as RDS and PostgreSQL.

• Nice to have: Experience in financial services or regulated environments.

• Nice to have: Experience with automated observability, data-quality, metadata, lineage, or data-catalog tools.

• Nice to have: Certifications in Snowflake, dbt, Apache NiFi, AWS, or data management.

🏝️ Benefits

• Comprehensive medical coverage for the employee, spouse, two children, and two parents.

• ₹6 lakhs annual medical coverage.

• Optional ₹5 lakhs medical top-up available with monthly deductions.

• Employer Provident Fund contribution of ₹1,800 per month.

• Annual performance-based bonus of up to 5% of base salary.

• Bucketlist point-based rewards redeemable for gift cards, experiences, and personalized perks.

• Recognition of milestones, achievements, and impact.

• Currently a remote work model, transitioning to a hybrid arrangement in the future.

• 15 annual leaves.

• 6 casual leaves.

• 12 sick leaves.

• Access to upskilling programs, mentorship, and professional development resources.

• Opportunities for internal mobility.

• Support for leadership development, industry certifications, and specialized training.

• Collaboration with global teams and exposure to international best practices.