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