Senior Data Engineer / Cloud Data Engineer

Job Details

• Job Title: Senior Data Engineer / Cloud Data Engineer
• Location: Indianapolis, IN
• Duration: 6 months
• GBaMS ReqID: 10955336
• Experience Required: 5–8 years
• Desirable Skill: AI & Gen AI – Products & Tools

Position Summary

• Develop, deploy, and optimize scalable:
  • Data pipelines
  • Data models
  • Analytics solutions
• Support enterprise-wide business insights and decision-making.
• Apply expertise in:
  • Cloud Data Engineering
  • Data Warehousing
  • Advanced SQL
  • Python / PySpark
  • Data Transformations
• Translate complex data into actionable business recommendations.
• Collaborate with cross-functional teams, preferably within the pharmaceutical or healthcare domain.

Core Responsibilities

Data Engineering & Pipeline Development

• Develop and maintain scalable ETL/ELT pipelines using:
  • Python
  • PySpark
  • SQL
• Support structured and unstructured data ingestion.
• Build robust cloud data infrastructure using:
  • Microsoft Fabric
  • Azure Synapse
  • Databricks
  • AWS
• Implement end-to-end automation for:
  • Data ingestion
  • Streaming
  • Scheduling
  • Monitoring
• Work with:
  • Azure Functions
  • Azure Data Factory
  • ADLS Gen2
  • Power BI
• Optimize large-scale big data architectures for performance and scalability.

Data Modeling & Architecture

• Design and maintain multidimensional data models, including:
  • Star Schema
  • Snowflake Schema
  • Fact tables
  • Dimension tables
  • Views
  • Stored procedures
• Manage complex datasets and ensure alignment with functional and non-functional requirements.
• Develop foundational knowledge of SAP S/4HANA and BW/4HANA data models to support financial analytics.

DevOps & Deployment

• Utilize GitHub and Azure DevOps for:
  • CI/CD
  • Version control
  • Automated deployments
• Manage artifact deployments across multiple environments.
• Perform:
  • Risk assessments
  • Impact analysis
• Implement process improvements and workflow automation.

Analytics & Business Partnership

• Partner with business stakeholders to:
  • Gather requirements
  • Understand business problems
  • Translate requirements into analytical solutions
• Develop analytics and reporting solutions supporting Global Finance transformation.
• Develop dashboards and BI solutions using:
  • Power BI
  • Tableau
• Translate analytical outcomes into actionable insights and KPIs.
• Troubleshoot data-related issues.
• Perform root cause analysis.

Required Qualifications

• 5–8 years of hands-on experience in:
  • Data Engineering
  • Cloud Data Warehousing
• Experience with cloud data platforms such as:
  • Azure Synapse
  • Microsoft Fabric
  • Databricks
  • AWS Redshift
  • Snowflake
• Expert-level SQL skills across:
  • Relational databases
  • Cloud data warehouses
• Strong Python and PySpark skills for:
  • Data transformation
  • Pipeline development
• Strong data modeling expertise, including:
  • Dimensional modeling
  • Fact and dimension tables
  • Normalization / denormalization
  • Views
  • Stored procedures
• Experience owning projects end-to-end.
• Ability to translate business problems into scalable analytical solutions.
• Experience designing and optimizing large-scale big data pipelines.
• Experience working with:
  • Structured datasets
  • Unstructured datasets
• Strong visualization skills using:
  • Power BI
  • Tableau
• Strong documentation and communication skills.
• Experience with:
  • Root cause analysis
  • Continuous improvement
  • Agile methodologies

Preferred Qualifications

• Experience with SQL and NoSQL databases, including:
  • AWS Redshift
  • PostgreSQL
  • Databricks
• Pharmaceutical or healthcare data experience.
• Cloud experience with:
  • AWS
  • Azure
• Microsoft Fabric experience is a strong advantage.
• CI/CD experience using:
  • GitHub
  • Azure DevOps
• Programming experience with:
  • Python
  • PySpark
  • R
  • Scala
  • Other scripting languages
• Exposure to AI and Generative AI products and tools.

Education

• Bachelor’s or Master’s degree in:
  • Technology
  • Computer Science
  • Engineering
  • Related field

Key Competencies

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management.
• High attention to detail and data quality.
• Ability to work effectively in fast-paced, dynamic environments.
• Strategic and critical thinking.
• Strong cross-functional collaboration and alignment.

Key Skills / Keywords

• Data Engineering
• Cloud Data Engineering
• ETL / ELT
• Azure
• Microsoft Fabric
• Azure Synapse
• Azure Data Factory
• ADLS Gen2
• Azure Functions
• Databricks
• AWS
• Redshift
• Snowflake
• SQL
• Python
• PySpark
• Power BI
• Tableau
• Data Modeling
• Dimensional Modeling
• Star Schema
• Snowflake Schema
• SAP S/4HANA
• BW/4HANA
• GitHub
• Azure DevOps
• CI/CD
• Big Data
• Data Warehousing
• AI & Generative AI
• Analytics
• Agile
• Root Cause Analysis