Required
- Snowflake experience
- ETL tools (ADF/Openflow/Matillion/dbt) experience
- Microsoft Fabric exposure and/or experience
- Reporting (Power BI/Sigma) exposure and/or experience
- Databases (PostgreSQL, Cosmos DB) exposure/learning knowledge
Responsibilities
- Build and maintain data pipelines for ingestion, transformation, and storage.
- Monitor and optimize data workflows for performance and reliability.
- Develop and manage ETL workflows to ensure timely and accurate data availability.
- Assist in the development and maintenance of Microsoft Fabric workspaces, supporting data integration, lakehouse architecture, and pipeline configurations, while contributing to the development of reports and dashboards that translate data into meaningful visualizations aligned with business needs.
- Contribute to the development and optimization of data architecture, collaborating with developers and data scientists to optimize queries and database design.
- Assist in the management and maintenance of enterprise database platforms including Snowflake, SQL Server, PostgreSQL, and Cosmos DB, supporting data storage, retrieval, and optimization tasks under the guidance of senior engineers.
- Work with data scientists and engineers to ensure data availability, quality, and consistency.
- Participate in overall database management and assist in troubleshooting data issues.
- Support the integration of AI and machine learning workflows by preparing, validating, and delivering clean datasets to support model training, evaluation, and deployment pipelines.
- Work closely with cross-functional teams to understand data needs and deliver solutions aligned with business requirements.
- Adhere to Architecture Review Board (ARB) and Change Advisory Board (CAB) processes and standards when contributing to data infrastructure or pipeline changes.
- Stay updated on emerging data technologies and best practices, contributing to a culture of continuous learning.
- Performs frequent complex SQL scripting that demonstrates expertise with relational tables using joins, unions and groupings.
- Provide technical troubleshooting as needed to assist clients, staff and vendors to resolve EDI/ETL processing challenges.
- Development of documented procedures associated with scheduled EDI/ETL events.
Qualifications
- Bachelor’s degree in data engineering, computer science, or a related field required (recent graduates and candidates nearing completion encouraged to apply), with 1–3 years of relevant experience. Candidates holding an associate’s degree must have a minimum of 5 years of experience.
- Working knowledge of SQL and database management tools.
- Proficiency in Python and other scripting languages.
- Hands-on experience with ETL concepts, data pipelines, and processes.
- Experience with or working knowledge of cloud platforms such as Azure, AWS, or GCP.
- Experience with version control systems (e.g., Git) and issue tracking systems (e.g., Jira).
- Familiarity with analytics reporting frameworks and platforms.
- Knowledge of integration patterns (e.g., SFTP, API, and file handling such as CSV).
- Knowledge of database management concepts (e.g., backup, query optimization, etc.).
- Familiarity with AI/ML concepts and tools or frameworks such as scikit-learn or vector databases, with an understanding of how data engineering supports AI-driven applications.
- Experience or Familiarity with Data Governance, Data Quality, Meta Data Management and Reference data management concepts and implementation.
- Must have exposure to a ticketing tool management or help desk function.
- Should possess excellent verbal and written communications, presentation, and effective listening skills.
- Strong troubleshooting, teamwork, and communication skills.
- Proven subscription to the company's core values of integrity, adaptability, service-focused, accountability, curiosity, and community.