Data Engineer

Location : India (Remote) Position Type:

Full Time

Key Responsibilities Data Pipeline Development & Support • Assist in building, testing, and maintaining ETL and ELT data pipelines. • Support data ingestion processes from multiple sources including APIs, relational databases, flat files, and third-party systems. • Validate pipeline outputs to ensure data completeness, accuracy, and consistency. • Monitor scheduled workflows and assist in resolving pipeline failures.

Data Transformation & Validation • Clean, transform, and standardize raw data using SQL and basic Python scripting. • Implement data validation checks to ensure accuracy and integrity. • Identify and troubleshoot data quality issues. • Support data reconciliation between source systems and target environments.

Database & Data Warehouse Support • Help maintain data warehouses and data lakes. • Write and optimize SQL queries for analytics and reporting workloads. • Support database performance optimization and workflow tuning. • Apply foundational data modeling concepts including normalization and dimensional modeling basics.

Collaboration & Documentation • Collaborate with data analysts, data scientists, and software engineers to understand data requirements. • Document data pipelines, data models, schemas, and transformation logic. • Follow established engineering standards and best practices.

Data Governance & Compliance • Ensure adherence to data governance standards and internal data handling policies. • Use, protect, and disclose patients' Protected Health Information (PHI) only in accordance with HIPAA regulations. • Maintain confidentiality and secure handling of sensitive healthcare data.

Required Qualifications Education • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience.

Experience • 3 years of experience in data engineering, software engineering, analytics engineering, or a related technical role.

Technical Skills SQL & Databases: • Strong SQL skills including joins, aggregations, subqueries, and query optimization. • Understanding of relational database systems such as PostgreSQL, MySQL, or SQL Server. • Familiarity with database schema design and indexing basics.

Programming: • Basic proficiency in Python or a similar programming language. • Ability to write scripts for data transformation and validation.

Data Engineering Concepts: • Foundational understanding of ETL and ELT processes. • Basic knowledge of data warehousing concepts including fact tables, dimension tables, and star schemas. • Familiarity with data modeling principles.

Analytical & Professional Skills • Strong analytical and problem-solving abilities. • Attention to detail in data validation and troubleshooting. • Ability to follow technical direction and collaborate within a team environment. • Clear written and verbal communication skills