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Data Engineer is responsible for designing, building, maintaining, and optimizing data solutions that collect, store, process, and make data accessible for analytics, reporting, and business decision-making. This role works closely with Data Product Owners, business stakeholders, analysts, and technical teams to develop scalable data pipelines, support data integration initiatives, and ensure the reliability, quality, and performance of enterprise data assets.

• Under general supervision, designs, build and maintains medium complexity data pipeline/ETL processes ensuring that the code follows latest coding practices and industry standards.  Work closely with other developers and team members to understand the system end-to-end and perform system analysis.   Responsible for creating data pipelines, ensuring data quality, and optimizing data infrastructure. Complete the work needed to implement features from the product backlog.
• Work closely with Product/Business Owner to understand stories and requirements from both Business and Technical perspective. Assist in building and maintaining scalable ETL/ELT pipelines. Support data ingestion from APIs, databases, and flat files. Clean, transform, and validate data to ensure accuracy and consistency. Write and optimize SQL queries for data extraction and reporting. 

Collaborate with data analysts and scientists to understand data needs. Monitor data workflows and troubleshoot pipeline issues. Document data processes and contribute to data engineering best practices. work closely with senior engineers, learning from their experience and expertise. Perform simple ad-hoc queries to answer specific business questions.

Key Responsibilities

• Implement features and enhancements from the data product backlog.
• Partner with Data Product Owners and business stakeholders to understand business and technical requirements.
• Assist in building and maintaining scalable ETL/ELT pipelines.
• Support data ingestion from APIs, relational databases, and flat files.
• Clean, transform, and validate data to ensure quality and consistency.
• Develop and optimize SQL queries for reporting and data extraction.
• Collaborate with data analysts and data scientists to meet analytical requirements.
• Monitor data workflows and troubleshoot data pipeline issues.
• Maintain documentation for data processes and technical solutions.
• Follow data engineering best practices and standards.
• Learn from and collaborate with senior engineers on enterprise initiatives.
• Perform ad hoc data analysis and queries to support business needs.

The knowledge, skills, abilities and experiences that are required for entry into this job include the following:

Required Skills & Experience

• 2+ years of relevant experience.
• Understanding of Relational Database Management Systems (RDBMS).
• Knowledge of data warehousing concepts, including star and snowflake schemas.
• Familiarity with version control systems such as Git or TFS.
• Understanding of data modeling principles.
• Hands on experience with ETL tools such as Talend, Informatica, or SSIS.
• Exposure to data virtualization tools such as Denodo
• Working knowledge of SQL, stored procedures, and database table design.
• Familiarity with scripting languages such as Python, Shell scripting.
• Experience with DataOps practices, CI/CD, and observability.

Preferred Qualifications

• Cloud platform experience (AWS, Azure, or GCP).
• Experience optimizing cost and performance in cloud data warehouses.
• Hands-on experience with Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink
• Experience Data catalog platforms (e.g., Collibra, Informatica IDMC, Alation)
• Experience with Data Observability Platforms  (e.g., Monte Carlo, Data dog, Atlan)

Education Level:

Degree or an equivalent combination of education and demonstrated related experience may be accepted in lieu of preferred level of education:

Bachelor

Preferred Discipline(s):  Computer Science, Information Technology

Other disciplines may be substituted for the preferred discipline(s) listed above.

Preferred:  Talend Certified, AWS Certified, Microsoft Certified, Azure Data Engineer

• Delivering at Pace: Acts with urgency to meet deadlines while maintaining quality, prioritizing workload effectively under pressure.
• Collaborative Teamwork: Actively supports colleagues, shares knowledge freely, and treats others with dignity and respect.
• Effective Communication: Tailors communication style to the audience, ensuring clarity and transparency in both successes and challenges.
• Ownership and Adaptability: Takes responsibility for outcomes and welcomes feedback for improvement.
• Ability to work independently
• Achievement orientation
• Self-starter
• Concern for quality
• Flexibility

No Testing Required