Lead Data Engineer (Snowflake)

Key Responsibilities

Data Pipeline Development

Develop and maintain ELT/ETL pipelines based on defined architectural and business requirements.

Implement processes for ingesting data from both structured and semi-structured sources, using web scraping, REST APIs, on-premises databases, and cloud storage.

Write, test, and optimize SQL/Python/Shell script-based data transformations.

Build and maintain data models (e.g., dimensional/star schema) according to design standards.

Ensure pipelines are scheduled, monitored, and operating reliably in production environments.

Snowflake Development & Optimization

Develop and manage tables, views, tasks, streams, and transformations within Snowflake.

Optimize queries for performance, scalability, and cost efficiency under architectural guidance.

Support performance tuning efforts and resolve data processing bottlenecks.

Adhere to enterprise naming conventions, coding standards, and governance policies.

Data Quality, Security & Compliance

Implement data validation rules, reconciliation checks, and automated quality controls.

Support the implementation of data security, privacy, and access control standards.

Investigate and resolve data discrepancies and production issues, create proactive alerts.

Perform root cause analysis on data failures and implement corrective actions.

Maintain thorough technical documentation for pipelines, datasets, and transformations.

Collaboration & Execution

Partner with Analytics and BI teams to deliver curated, trusted datasets for dashboards and reporting.

Support testing and validation of new data assets prior to production release.

Assist in maintaining CI/CD processes and version control for data engineering assets.

Continuous Improvement

Apply best practices in data engineering and Snowflake development.

Identify opportunities to improve pipeline efficiency, reliability, and automation.

Stay current with Snowflake capabilities and modern data engineering tools and techniques.

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Qualifications & Experience

Experience

5+ years of experience in data engineering, data development, or BI development roles.

Hands-on experience writing and optimizing complex SQL queries.

Experience working with relational databases and data warehouse concepts.

Experience with cloud data platforms; Snowflake experience strongly preferred.

Technical Skills

Strong SQL skills (joins, aggregations, window functions, performance tuning).

Experience with Snowflake data warehousing concepts and implementation.

Familiarity with ELT/ETL processes and transformation frameworks.

Basic scripting ability in Python or similar language (preferred).

Understanding of dimensional modeling (fact and dimension tables).

Familiarity with version control systems (e.g., Git).

Preferred

Experience

Experience with modern data stack tools (e.g., Fivetran, orchestration tools).

Experience working in a managed services, SaaS, or data-driven enterprise environment.

Exposure to data governance and information management frameworks.

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field preferred.

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Core Competencies

Strong attention to detail and commitment to data accuracy and integrity.

Ability to execute against defined standards and technical direction.

Analytical thinking and structured problem-solving skills.

Clear communication within technical and cross-functional teams.

Accountability for deliverables, quality, and deadlines.

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What Success Looks Like

Data pipelines are implemented accurately according to architectural specifications.

Data transformations are performant, scalable, and reliable.

Data quality and validation controls are embedded within pipelines.

Documentation is complete, organized, and maintainable.

Analytics and business teams consistently receive trusted, timely, and usable data.

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This role offers the opportunity to contribute to a growing enterprise data ecosystem at a leading tech-enabled managed services organization. You will gain hands-on experience building a modern cloud data platform that directly supports operational excellence and strategic decision-making across Opensity Solutions.