Data Engineer

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data workflows using modern cloud and big data technologies.
• Collaborate with data analysts, business stakeholders, and engineering teams to deliver reliable data solutions.
• Develop data integration processes across multiple healthcare and enterprise systems.
• Ensure data quality, integrity, governance, and security standards are maintained.
• Monitor and troubleshoot data pipelines and production jobs.
• Support reporting, analytics, and business intelligence initiatives.
• Participate in performance tuning and optimization of databases and data processing systems.

Qualifications

• 2+ years of experience as a Data Engineer or in a related data-focused role.
• Strong experience with SQL and relational databases.
• Hands-on experience with Python, PySpark, or Scala.
• Experience working with ETL tools and data pipeline development.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience with big data technologies like Spark, Hadoop, or Databricks is preferred.
• Knowledge of data warehousing concepts and dimensional modeling.
• Strong analytical, problem-solving, and communication skills.
• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
• Preferred: Healthcare domain experience preferred, Exposure to HIPAA-compliant environments is an advantage.
• Strong analytical and problem-solving skills.

What We Offer

• Opportunity to work with a Fortune 500 Healthcare organization.
• Exposure to enterprise-scale cloud and data engineering projects.
• Collaborative and technology-driven work environment.
• Competitive compensation package.
• Long-term growth and career advancement opportunities.

Skills

• sql
• python
• healthcare
• cloud
• data
• analytics
• azure
• aws
• big data
• data engineering
• etl
• gcp