Data Engineer

About the Role

Key Responsibilities

• Understand the Enterprise data systems and acquire knowledge on the relevant processes needed for project delivery.
• Participate in project estimation process and provide inputs to Tech Lead.
• Participate in Agile scrum activities and project status meetings regularly.
• Participate in User story grooming and design discussions with technical lead.
• Analyze complex data structures from disparate data sources and design large-scale data engineering pipelines.
• Use strong programming skills to build robust data pipelines for ETL processes, design database systems, and develop data processing tools.
• Perform all Data Engineering activities including EDW/ETL project development, testing, and deployment.
• Work closely with developers on ETL jobs and pipelines development.
• Create project processes and automation by integrating involved components.
• Document data engineering processes, workflows, and systems for reference and knowledge sharing.
• Implement data quality checks and validation processes to ensure data accuracy, completeness, and consistency.
• Collaborate with team members for business solutions and implementation.

Requirements

• 1+ years of experience in executing Data warehousing ETL projects.
• 1+ years of experience with Python.
• 1+ years of experience with SQL.
• 1+ years of experience with ETL/ELT and building high-volume batch/realtime data pipelines.
• 1+ years of hands-on experience with bash shell scripts, UNIX utilities, and UNIX commands.
• 1+ years of hands-on experience with a major cloud platform (GCP, AWS, or Azure).

Nice to Have

• Experience with complex systems and solving challenging analytical problems.
• Strong collaboration and communication skills within and across teams.
• Knowledge of data visualization and reporting tools.
• Implementation experience in building real-time or near real-time data pipelines using pub/sub or change data capture.
• Knowledge of AI/ML model building using Python libraries and data wrangling/data preparation experience.
• Experience with Git, CI/CD pipelines, and DevOps principles.
• Understanding of software development methodologies including waterfall and agile.
• Ability to leverage multiple tools and programming languages to analyze and manipulate data from disparate sources.
• Knowledge of API development, microservices, and SOA.
• Experience with schema design and dimensional data modeling.
• Google Professional Data Engineer Certification.
• Formal SAFe and/or agile experience.
• Previous healthcare domain knowledge.
• Experience designing, building, and maintaining data processing systems.
• Experience architecting and building data warehouses and data lakes.

Qualifications

• Bachelor's Degree or equivalent work experience in Computer Science, Information Systems, Data Engineering, Data Analytics, Machine Learning, or related field.
• Master's Degree preferred.

Benefits & Perks

• Affordable medical plan options.
• A 401(k) plan including matching company contributions.
• An employee stock purchase plan.
• No-cost programs including wellness screenings, tobacco cessation, weight management, confidential counseling, and financial coaching.
• Paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access, and other benefits depending on eligibility.