Azure Data Engineering Consultant

Optum; Hyderabad; Hybrid; INR 1,200,000 - 2,100,000; Full time

Job summary

Optum in Hyderabad invites a seasoned Data Engineer to lead end‑to‑end data pipelines across healthcare analytics. You will design, develop, test, deploy, and maintain data management solutions, driving data quality, governance, and reliable movement from source systems to data warehouses and marts.

The role emphasizes ETL/ELT with SQL, Python, Scala, and cloud tools, collaborating with analytics teams to enable BI and advanced analytics while reducing technical debt and ensuring security and

Qualifications

• Bachelor’s degree in information technology, engineering, math, computer science, analytics or related field.
• 5+ years of combined experience in data engineering, ingestion, normalization, transformation, aggregation, structuring, and storage.
• 5+ years of combined experience with relational, dimensional or non-relational data storage systems.
• 5+ years designing ETL/ELT solutions using Informatica, DataStage, SSIS, PL/SQL, or T-SQL.
• 5+ years managing data assets using SQL, Python, Scala, VB.NET or similar.
• 3+ years working with healthcare data to support healthcare organizations.
• 3+ years in Microsoft Azure Cloud, Azure Data Factory, Databricks, Spark, Scala/Python, ADO.

Responsibilities

• Support the full data engineering lifecycle including research, proof of concepts, design, development, testing, deployment, and maintenance of data management solutions
• Utilize knowledge of various data management technologies to drive data engineering projects
• Lead data acquisition efforts to gather data from source systems to hydrate client data warehouse and power analytics
• Leverage ETL/ELT to pull relational and dimensional data to support DataMarts and reporting
• Eliminate unwarranted complexity and interdependencies
• Detect data quality issues, identify root causes, implement fixes, and manage audits
• Implement, modify, and maintain data integration efforts that improve data efficiency and value
• Evolve best practices for data acquisition, transformation, storage, and aggregation
• Create data transformations addressing business requirements
• Partner with analytics to recommend data system changes and data platform architecture
• Support modern data framework enabling BI reporting and advanced analytics
• Prepare high level and detailed design documents for data ingestion, transformation and movement
• Use DevOps tools for code versioning and deployment
• Use data pipeline monitoring tools to detect integrity issues
• Troubleshoot, maintain and optimize solutions and respond to issues
• Support debt reduction, process transformation, and optimization
• Contribute to standards for data definitions and governance

Education

Bachelor’s Degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)

Tools

Informatica

DataStage

SSIS

PL/SQL

T-SQL

Azure Data Factory

Databricks

Spark

Python

SQL

Job description

Primary Responsibilities:

• Support the full data engineering lifecycle including research, proof of concepts, design, development, testing, deployment, and maintenance of data management solutions
• Utilize knowledge of various data management technologies to drive data engineering projects
• Lead data acquisition efforts to gather data from various structured or semi-structured source systems of record to hydrate client data warehouse and power analytics across numerous health care domains
• Leverage combination of ETL/ELT methodologies to pull complex relational and dimensional data to support loading DataMarts and reporting aggregates
• Eliminate unwarranted complexity and unneeded interdependencies
• Detect data quality issues, identify root causes, implement fixes, and manage data audits to mitigate data challenges
• Implement, modify, and maintain data integration efforts that improve data efficiency, reliability, and value
• Leverage and facilitate the evolution of best practices for data acquisition, transformation, storage, and aggregation that solve current challenges and reduce the risk of future challenges
• Effectively create data transformations that address business requirements and other constraints
• Partner with the broader analytics organization to make recommendations for changes to data systems and the architecture of data platforms
• Support the implementation of a modern data framework that facilitates business intelligence reporting and advanced analytics
• Prepare high level design documents and detailed technical design documents with best practices to enable efficient data ingestion, transformation and data movement
• Leverage DevOps tools to enable code versioning and code deployment
• Leverage data pipeline monitoring tools to detect data integrity issues before they result into user visible outages or data quality issues
• Leverage processes and diagnostics tools to troubleshoot, maintain and optimize solutions and respond to customer and production issues
• Continuously support technical debt reduction, process transformation, and overall optimization
• Leverage and contribute to the evolution of standards for high quality documentation of data definitions, transformations, and processes to ensure data transparency, governance, and security
• Ensure that all solutions meet the business needs and requirements for security, scalability, and reliability
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so.

Builder Responsibilities:

Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making.

Required Qualifications:

• Bachelor’s Degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)
• 5+ years of combined experience in data engineering, ingestion, normalization, transformation, aggregation, structuring, and storage
• 5+ years of combined experience working with industry standard relational, dimensional or non-relational data storage systems
• 5+ years of experience in designing ETL/ELT solutions using tools like Informatica, DataStage, SSIS , PL/SQL, T-SQL, etc.
• 5+ years of experience in managing data assets using SQL, Python, Scala, VB.NET or other similar querying/coding language
• 3+ years of experience working with healthcare data or data to support healthcare organizations
• 3+ years of experience in Micorsoft Azure Cloud, Azure Data Factory, Data Bricks, Spark, Scala / Python , ADO.