Senior Data Engineer

Key Responsibilities

• Snowflake Instance Management: Set up, configure, and manage between three to four new Snowflake data warehouse instances per quarter, tailored to support emerging products and analytics requirements.
• Segment Integration: Establish and maintain reliable connections between Segment and Snowflake, ensuring that data flow is accurate, timely, and consistent across all integrated products.
• Feature Exploration and Adoption: Proactively learn about new and existing Segment features. Assess, test, and implement these features to continuously improve the quality and utility of data being funneled into Snowflake.
• Collaboration with Data Engineers: Work closely with two data engineers based in Dallas, who support the Marketing team’s Segment/Snowflake needs. Share updates, insights, and lessons learned, and align on initial setup, schema design, and best practices to deliver a unified analytics environment.
• Team Meetings and Communication: Attend one or two meetings each week, primarily in the US time zone. These may include the weekly analytics team meeting, ad hoc meetings with product engineers, or other strategic discussions as needed.

Primary Duties & Tasks

• Coordinate with product managers and analytics leads during the design and rollout of new Snowflake instances, ensuring each instance meets product-specific and organizational requirements.
• Evaluate business needs and recommend optimal schema designs and data models in Snowflake, in partnership with data engineers and analytics stakeholders.
• Develop and maintain automated pipelines for ingesting, transforming, and validating data from Segment into Snowflake.
• Monitor data pipelines for latency, errors, and data quality issues, responding swiftly to resolve problems and minimize downtime.
• Document setup processes, data flows, and schema definitions to ensure ongoing maintainability and knowledge sharing across teams.
• Stay current on developments in Segment and Snowflake platforms, exploring pilot programs or beta features that could provide analytic advantages.
• Propose and implement new processes to streamline data onboarding for future products, reducing manual effort and increasing reliability.
• Participate in code reviews and contribute to the documentation and refinement of engineering standards related to data integration.
• Communicate findings, risks, and opportunities clearly to both technical and non-technical stakeholders.

Required Skills & Qualifications

• Technical Expertise: Demonstrated experience setting up and managing Snowflake data warehouse environments, including user roles, security, and advanced data modeling.
• Segment Mastery: Familiarity with Segment (or similar CDP tools), including source and destination setup, event tracking, and feature utilization to ensure high data fidelity.
• Data Engineering Fundamentals: Proficiency in SQL, data transformation, and ETL pipeline management. Understanding of data quality best practices and troubleshooting methodologies.
• Collaboration & Communication: Proven ability to collaborate with remote engineers and cross-functional teams, and to communicate complex technical concepts with clarity and confidence.
• Documentation & Process: Strong skills in documenting procedures, data schemas, and integration standards for a technical audience.
• Project Management: Organized and detail-oriented, able to manage multiple parallel product launches and integration tasks efficiently.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
• Experience working in a fast-paced, product-centric environment and supporting marketing analytics teams.
• Understanding of privacy requirements (such as GDPR or CCPA) as they relate to data collection and warehousing.
• Familiarity with additional data pipeline tools (e.g., dbt, Airflow) and cloud environments (AWS, GCP, or Azure).
• Experience with business intelligence platforms and data visualization tools is a plus.

Working Environment & Schedule

• This role is based out of Hyderabad, with the expectation of regular virtual collaboration with team members in Dallas and across the US.
• Availability for one or two key meetings per week in US time zones is required. Flexibility to accommodate the needs of product engineers and analytics teams is a must.