Data Engineer (ONSITE)

The Data Engineer is responsible for designing, and building data pipelines, data models, and foundational data infrastructures. The Data Engineer enables downstream analytics, reporting, and early-stage machine learning use cases by ensuring clean, well-structured, and governed data assets. The Data Engineer works with senior engineers, analysts, and data scientists to create scalable and trustworthy data environments.

• Bachelor’s degree in computer science, Information Systems, Data Engineering, Applied Math, or related discipline required
• Professional or relevant internship/project experience in a data-focused role (e.g., Data Engineering, Software Engineering, or Data Analytics) role required
• Academic coursework or certifications in data engineering preferred
• Practical hands-on experience through Capstone or internship preferred
• Preferred skills and competencies:
  • SQL for queries, joins, aggregations, and performance optimization basics
  • Python or Java for data manipulation and automation
  • Data warehouse concepts (dimensional modeling, facts, dimensions)
  • ETL/ELT frameworks and orchestration tools (Airflow, DBT, etc.)
  • Cloud platforms (AWS, Azure, or GCP)
  • Git-based version control
  • Feature engineering concepts and ML dataset preparation
  • Data serialization formats (JSON, Parquet, Avro)
  • Foundational understanding of ML workflows and model lifecycle
  • Analytical mindset with attention to data accuracy and completenes
  • Ability to collaborate with data engineers, data scientists, and business teams
  • Clear written documentation of data transformation logic
  • Curiosity to learn new tools, frameworks, and cloud technologies
  • Strong debugging and problem-solving skills

• Builds and maintains ETL/ELT pipelines that ingest, transform, and deliver structured and semi-structured data
• Develops SQL queries to support dashboards, analytics, and self-service data exploration
• Supports data quality checks, validation rules, and anomaly detection for model-ready datasets
• Partners with data scientists to prepare training and inference datasets, including feature extraction and feature store integration
• Contributes to metadata documentation, lineage tracking, and data catalog updates
• Assists in integrating data from core systems, APIs, cloud platforms, and third-party sources
• Participates in Agile ceremonies, sprint planning, and backlog refinement sessions.
• Learns best practices in data security, privacy, compliance, and responsible AI data standards
• Performs other duties as needed upon request by immediate supervisor