Data Engineer

Our mission is to provide   modernized technology platforms,   elevated technology support, and   valuable insights, empowering our clients to excel in what they do best.

POSITION SUMMARY:

Opensity is seeking a driven and enthusiastic Data Engineer to help build and scale our enterprise data foundation from the ground up. We are in an exciting phase of developing a modern, cloud-based data infrastructure that will unify data across business units and power analytics, reporting, and operational intelligence.
This is a hands-on, execution-focused role. You will design, code, test, and operationalize scalable data solutions that support dashboards, reporting, and advanced analytics across the organization. You will play a key role in shaping our enterprise data warehouse, automating critical processes, and embedding strong data security and privacy standards into everything we build.
If you are passionate about building clean, reliable, and well-engineered data systems—and want to contribute to a rapidly evolving enterprise data platform—this is an opportunity to make a meaningful impact.

ROLES & 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.

KNOWLEDGE, SKILLS & ATTRIBUTES:

• 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.

QUALIFICATIONS:

Education:

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

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).