Senior Data Engineer​/Cloud Data Engineer

Senior Data Engineer / Cloud Data Engineer

Location:

Indianapolis, IN

Duration: 6 months

Experience

Required:

5–8 years

Desirable Skill: AI & Gen AI – Products & Tools

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 / Py Spark
• Data Transformations

Translate complex data into actionable business recommendations.

Collaborate with cross-functional teams, preferably within the pharmaceutical or healthcare domain.

Develop and maintain scalable ETL/ELT pipelines using:

• Python
• Py Spark
• 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.

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/4

HANA and BW/4

HANA data models to support financial analytics.

Utilize Git Hub and Azure Dev Ops for:

• CI/CD
• Version control
• Automated deployments

Manage artifact deployments across multiple environments.

Perform:

• Risk assessments
• Impact analysis

Implement process improvements and workflow automation.

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.

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

Experience with SQL and No

SQL 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:

• Git Hub
• Azure Dev Ops

Programming experience with:

• Python
• Py Spark
• R
• Scala
• Other scripting languages

Exposure to AI and Generative AI products and tools.

Bachelor's or Master's degree in:

• Technology
• Computer Science
• Engineering
• Related field

• 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.

• 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
• Py Spark
• Power BI
• Tableau
• Data Modeling
• Dimensional Modeling
• Star Schema
• Snowflake Schema
• SAP S/4
  
  HANA
• BW/4
  
  HANA
• Git Hub
• Azure Dev Ops
• CI/CD
• Big Data