Description

Key Responsibilities

• Design, develop, test, and maintain data pipelines and integrations across multiple platforms.
• Build and optimize systems for data ingestion, transformation, and processing of large datasets.
• Support the full data lifecycle, from data acquisition and ingestion through the creation of analytics-ready datasets.
• Build and maintain scalable data products incrementally while integrating and managing datasets from multiple sources.
• Ensure high-quality and reliable data solutions through testing, validation, monitoring, and observability practices.
• Apply data modeling techniques and data structures appropriate for transactional and analytical use cases.
• Partner with upstream and downstream teams to ensure data is effectively modeled, governed, integrated, and delivered.
• Identify and address data quality issues, performance bottlenecks, and technical debt.
• Follow and promote best practices for version control, automated testing, documentation, and code quality.
• Participate in technical design discussions and contribute to solution architecture and design with guidance.
• Apply security policies and standards during development and support risk mitigation efforts.
• Create and maintain documentation for data processes, models, integrations, and pipelines.
• Collaborate with team members through code reviews, pair programming, and knowledge sharing.
• Support business intelligence and reporting initiatives using enterprise data platforms and reporting tools.
• Effectively communicate technical strategies, designs, and recommendations to stakeholders at all levels of the organization.
• Provide on-call support when required.

Required Qualifications

• Bachelor's degree with 6–10 years of related work experience, or a Master's degree in a related field with 2–8 years of related work experience.
• Proven experience as an IT professional.
• Experience with a variety of data modeling techniques and data structures.
• Experience building and operating systems for data extraction, ingestion, and processing of large datasets.
• Experience optimizing data for analytics and data science use cases.
• Experience building data products and integrating datasets from multiple sources.
• Knowledge and direct experience with business intelligence and reporting tools.
• Strong leadership and presentation skills.
• Advanced planning, organizational, problem-solving, analytical, and decision-making skills.
• Strong written and verbal communication skills.
• Ability to collaborate effectively with technical and business teams.
• Ability to communicate technical strategies and designs to all levels of the organization.
• High degree of accuracy and ability to maintain confidentiality.

Preferred Qualifications

• Experience with modern enterprise data platforms such as Snowflake.
• Familiarity with data quality tools and practices such as Ataccama.
• Experience with data integration tools such as:
  • AWS Glue
  • Fivetran
  • Informatica IDMC
• Experience with transactional/source-system data modeling, including Third Normal Form (3NF).
• Experience with data pipeline monitoring, observability, and reliability.
• Experience implementing data quality, validation, and governance practices.
• Experience working in modern cloud-based data environments.

Technical Focus

• Data Engineering
• Data Pipelines
• Data Ingestion
• Data Integration
• Data Transformation
• Data Modeling
• Transactional Data
• Analytics & Data Science
• Business Intelligence
• Data Quality
• Data Governance
• Pipeline Monitoring & Observability
• Snowflake
• AWS Glue
• Fivetran
• Informatica IDMC
• Ataccama

Key Skills

Education

Bachelor's or Master's degrees