Data Engineer (Snowflake)

Snowflake & Segment Data Integration
Specialist

Empowering Seamless Data Infrastructure for Marketing
& Product Analytics

Are you passionate about data infrastructure and eager to
empower analytics teams to turn information into insightsJoin our dynamicorganization as a Snowflake & Segment Data Integration Specialist. In thispivotal role, youll be at the intersection of product data, marketinganalytics, and data engineeringensuring the seamless flow and integrity ofdata that drives our business forward.

Snowflake Instance Management: Set up,
configure, and manage between three to four new Snowflake data warehouseinstances per quarter, tailored to support emerging products and analyticsrequirements.

Segment Integration: Establish and maintain
reliable connections between Segment and Snowflake, ensuring that data flow isaccurate, timely, and consistent across all integrated products.

Feature Exploration and Adoption: Proactively
learn about new and existing Segment features. Assess, test, and implementthese features to continuously improve the quality and utility of data beingfunneled into Snowflake.

Collaboration with Data Engineers: Work closely
with two data engineers based in Dallas, who support the Marketing teamSegment/Snowflake needs. Share updates, insights, and lessons learned, andalign on initial setup, schema design, and best practices to deliver a unifiedanalytics environment.

Team Meetings and Communication: Attend one or
two meetings each week, primarily in the US time zone. These may include theweekly analytics team meeting, ad hoc meetings with product engineers, or otherstrategic discussions as needed.

Coordinate with product managers and analytics
leads during the design and rollout of new Snowflake instances, ensuring eachinstance meets product-specific and organizational requirements.

Evaluate business needs and recommend optimal
schema designs and data models in Snowflake, in partnership with data engineersand 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 minimizedowntime.

Document setup processes, data flows, and schema
definitions to ensure ongoing maintainability and knowledge sharing acrossteams.

Stay current on developments in Segment and
Snowflake platforms, exploring pilot programs or beta features that couldprovide analytic advantages.

Propose and implement new processes to
streamline data onboarding for future products, reducing manual effort andincreasing reliability.

Participate in code reviews and contribute to
the documentation and refinement of engineering standards related to dataintegration.

Communicate findings, risks, and opportunities
clearly to both technical and non-technical stakeholders.

Technical Expertise: Demonstrated experience
setting up and managing Snowflake data warehouse environments, including userroles, security, and advanced data modeling.

Segment Mastery: Familiarity with Segment (or
similar CDP tools), including source and destination setup, event tracking, andfeature utilization to ensure high data fidelity.

Data Engineering Fundamentals: Proficiency in
SQL, data transformation, and ETL pipeline management. Understanding of dataquality best practices and troubleshooting methodologies.

Collaboration & Communication: Proven
ability to collaborate with remote engineers and cross-functional teams, and tocommunicate complex technical concepts with clarity and confidence.

Documentation & Process: Strong skills in
documenting procedures, data schemas, and integration standards for a technicalaudience.

Project Management: Organized and
detail-oriented, able to manage multiple parallel product launches andintegration tasks efficiently.

Bacheloror Masterdegree 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.

This role is based out of Hyderabad, with the
expectation of regular virtual collaboration with team members in Dallas andacross the US.