Senior Data Engineer

Accountabilities

• • Design, build, maintain, and optimize end-to-end ETL and ELT pipelines for high-volume advertising data.
  • Ingest data from multiple advertising and demand-side platforms, including Adform, Google Ads, and Meta Marketing API, into Snowflake.
  • Develop and optimize Snowflake stored procedures supporting data rollups, attribution calculations, reporting, and analytics aggregations.
  • Manage AWS Lambda functions using Node.js and Java for real-time and batch data processing, including pixel event ingestion and Snowflake notifications.
  • Design and maintain Snowflake data models supporting dashboard reporting, attribution analysis, analytics, and AI-driven product capabilities.
  • Build and manage S3-based data lake architecture for raw data storage, ingestion, and processing.
  • Support SQS-based asynchronous workflows for report generation and data-processing queues.
  • Monitor data pipeline health and proactively troubleshoot issues affecting data accuracy, reliability, or freshness.
  • Implement data quality checks, monitoring, and alerting mechanisms to detect pipeline failures and data anomalies.
  • Collaborate with engineering teams to integrate new data sources, advertising platforms, and DSP connections.
  • Document data flows, schemas, pipeline architecture, and operational processes to ensure maintainability and knowledge sharing.
  • Mentor junior engineers and contribute to technical decisions related to data architecture, engineering practices, and platform scalability.
  • Balance hands-on engineering responsibilities with technical leadership and cross-functional collaboration.

  Requirements

  • 5+ years of professional experience in data engineering or a closely related field.
  • Proven experience designing, building, and owning production-grade data pipelines from ingestion through transformation and delivery.
  • Strong experience working with Snowflake, including data modeling, stored procedures, aggregations, and performance optimization.
  • Hands-on experience with AWS data and cloud services, particularly S3, Lambda, and SQS.
  • Experience working with PostgreSQL or other relational databases.
  • Strong understanding of ETL/ELT architecture, data ingestion, transformation, orchestration, and data quality practices.
  • Experience processing high-volume or near-real-time datasets is highly valuable.
  • Familiarity with APIs and integrating data from third-party platforms and external data sources.
  • Experience with Node.js and/or Java for cloud-based data processing is advantageous.
  • Ability to mentor junior engineers and influence technical decisions related to data architecture.
  • Strong analytical and troubleshooting skills, with the ability to investigate complex data and pipeline issues.
  • Comfortable owning projects independently while collaborating effectively with engineering and cross-functional teams.
  • Ability to manage multiple priorities, meet deadlines, and operate effectively in a fast-paced environment.
  • Strong written and verbal communication skills, with a proactive and collaborative approach.
  • Comfortable working primarily between 9:30 AM and 6:30 PM ET.
  • Adaptable, curious, research-oriented, and comfortable experimenting with new technologies and approaches.
  • A player/coach mindset, combining hands-on execution with technical leadership and mentorship.
  • Ability to receive and provide direct feedback constructively.
  • Entrepreneurial mindset, creative confidence, and a strong sense of ownership.

  Benefits

  • Competitive salary.
  • Paid time off.
  • Fully remote work arrangement from India.
  • Opportunity to work on high-volume advertising and AI-driven data products.
  • Exposure to modern data infrastructure built around Snowflake and AWS.
  • Opportunity to shape data architecture and engineering practices as the platform scales.
  • Mentorship and technical leadership opportunities.
  • Collaborative, international, and fast-paced engineering environment.
  • Opportunity to work with complex datasets involving real-time advertising, attribution, analytics, and multiple external platforms.