Actual
Years
Experience

Years
Experience
Needed

Required/
Preferred

Skills/Experience

8

Required

Implement ETL/ELT workflows for both structured and unstructured data

8

Required

Collaborate with cross-functional teams including data scientists, analysts, and stakeholders

8

Required

Design and maintain data models, schemas, and database structures to support analytical and operational use cases

8

Required

Implement data validation and quality checks to ensure accuracy and consistency

8

Required

Contribute to data governance initiatives, including metadata management, data lineage, and data cataloging

8

Required

Implement data security measures, including encryption, access controls, and auditing; ensure compliance with regulations and best practices

8

Required

Working in agile, multicultural environments

4

Required

Automate deployments using CI/CD tools

4

Required

Evaluate and implement appropriate data storage solutions, including data lakes (Azure Data Lake Storage) and data warehouses

4

Required

Proficiency in Python and R programming languages

4

Required

Strong SQL querying and data manipulation skills

4

Required

Experience with Azure cloud platform

4

Required

Experience with DevOps, CI/CD pipelines, and version control systems

4

Required

Strong troubleshooting and debugging capabilities

3

Required

Design and develop scalable data pipelines using Apache Spark on Databricks

3

Required

Optimize Spark jobs for performance and cost efficiency

3

Required

Integrate Databricks solutions with cloud services (Azure Data Factory)

3

Required

Ensure data quality, governance, and security using Unity Catalog or Delta Lake

3

Required

Deep understanding of Apache Spark architecture, RDDs, DataFrames, and Spark SQL

3

Required

Hands-on experience with Databricks notebooks, clusters, jobs, and Delta Lake

2

Required

Build AI accelerators and reusable components to boost development teams productivity.

2

Required

Implement Gen AI / LLM application and utilities (Agentic AI, Harness / Prompt engineering, RAG)

2

Required

Implement AI application governance, observability and evaluation framework

2

Required

Design & Implement vector stores for knowledge bases and agent memory

2

Required

Integrate AI applications / utils / tools with enterprise traceability and SIEM tools

2

Required

Knowledge of ML libraries (MLflow, Scikit-learn, TensorFlow)

1

Preferred

Databricks Certified Associate Developer for Apache Spark

1

Preferred

Azure Data Engineer Associate