Senior Data Engineer

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

📋 Description

• Design, develop, and sustain ETL/ELT pipelines for both structured and unstructured data sourced from internal and external origins.

• Utilize AI-enhanced development tools to expedite pipeline creation, produce transformation logic, and automate standard coding tasks.

• Construct and enhance data warehouses and marts tailored for analytics, reporting, and product applications.

• Create, implement, and manage conceptual, logical, and physical data models.

• Extract data from APIs, SaaS platforms, and internal systems into the primary data platform.

• Develop and uphold dependable connectors and ingestion frameworks that accommodate schema changes, rate limitations, and error recovery.

• Establish validation, schema management, and documentation processes to ensure data accuracy and compliance.

• Leverage AI tools for data profiling, anomaly detection, and automated documentation of lineage and transformations.

• Assess and incorporate emerging AI tools into the team's data development workflow.

• Create and support agentic workflows and multi-step automated processes that operate on real-time data.

• Implement AI-assisted analysis to troubleshoot pipeline failures, enhance query performance, and pinpoint data quality concerns.

• Monitor and optimize pipeline and warehouse performance for scalability and cost-effectiveness.

• Establish logging, monitoring, and alert systems for data jobs.

• Enforce data security and privacy measures in line with financial regulatory standards.

• Supply clean and consistent datasets for analysts, product managers, and operational teams.

• Collaborate with product managers, data scientists, and full stack engineers to ensure data models meet business requirements.

⛳️ Requirements

• 5+ years of experience in data engineering or a similar backend data-focused position.

• Strong SQL and Python development expertise for data transformation and automation tasks.

• Familiarity with contemporary ETL/ELT frameworks such as dbt.

• Proficient in cloud platforms (AWS preferred) and serverless data services.

• Extensive experience with data warehouse technologies (Snowflake preferred).

• Proficient in API integrations and data ingestion from third-party systems.

• Skilled in data modeling techniques (Kimball/Star schema, Data Vault).

• Regularly utilize AI-powered development tools (e.g., Cursor, GitHub Copilot, Claude Code, or similar) to enhance data pipeline development, debugging, or documentation.

• Proven history of successfully delivering production-grade data pipelines at scale.

• Experience with implementing CI/CD practices for data workflows.

• Experience in close collaboration with product managers, data scientists, and full stack engineers.

• Startup mindset: hands-on, innovative, and adaptable to a fast-paced environment.

• Preferred: Experience in developing agentic workflows and orchestrating multi-step automated processes that respond to real-time data.

• Preferred: Knowledge of data engineering patterns and infrastructure necessary for AI-powered tools and automation platforms.

• Preferred: Experience working with financial datasets and APIs within a high-compliance setting.

• Preferred: Understanding of data privacy regulations such as GDPR and CCPA.

• Preferred: Experience in prompt engineering for code generation, data transformation logic, or creating AI-driven data workflows.

🏝️ Benefits

• Competitive salary.

• Unlimited PTO.

• Remote-first with flexible working hours.

• Up to $2,000 per year for professional development.

• Home office setup stipend.