DE&A - Core - Advanced Data Engineering - Business Analyst @ Zensar

Core Platforms

• Databricks Unity Catalog, Delta Live Tables, Databricks SQL, Spark optimization, job orchestration

• Tableau calculated fields, LOD expressions, data blending, published data sources, Tableau Server/Cloud

• Python pandas, NumPy, PySpark, scikit-learn, SQLAlchemy, Airflow/Prefect integration

Large Language Models (LLMs)

Hands-on familiarity with leading LLMs and their APIs, including but not limited to:

• SemiKong (semiconductor-domain LLM) preferred differentiator for this role

• OpenAI GPT-4 / GPT-4o

• Anthropic Claude (claude-3 / claude-sonnet family)

• Google Gemini (1.5 Pro / Flash)

• Meta LLaMA 3 / LLaMA 3.1

• Mistral / Mixtral

• Cohere Command R+

• Falcon, Phi-3, and other open-weight models

• Prompt engineering, RAG architecture, LangChain / LlamaIndex for applied analytics use cases

Data SQL

• Advanced SQL window functions, CTEs, query optimization across Databricks SQL, Snowflake, or similar

• Data modeling concepts star/snowflake schemas, dimensional modeling

• Experience with large-scale structured and semi-structured datasets (JSON, Parquet, Delta format)

Additional Technical Exposure (Preferred)

• Cloud platforms AWS (S3, Glue, Redshift), GCP (BigQuery), or Azure (Synapse, ADLS)

• Version control Git/GitHub for script management and collaboration

• Basic ML model evaluation and feature engineering in Python

• Familiarity with CI/CD pipelines for analytics/ML assets

• 10+ years of professional experience as a Data Analyst, Analytics Engineer, or closely related role.

• Proven track record delivering analytical projects in semiconductor, manufacturing, or hi-tech industry preferred.

• Strong portfolio demonstrating Databricks and Tableau work at scale.

• Demonstrated hands-on usage of LLMs in a professional or research context not just theoretical knowledge.

• Experience working in agile / scrum teams within large enterprise environments.

• Bachelors degree (or higher) in Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field.

• Strong business acumen ability to translate data findings into clear, actionable recommendations for non-technical stakeholders.

• Excellent verbal and written communication skills in English.

• Self-starter mindset; comfortable with ambiguity and evolving requirements.

• High attention to detail and commitment to data accuracy and integrity.

• Collaborative team player with the ability to work across global time zones as needed.

• Design, build, and maintain end-to-end data pipelines and analytical workflows on Databricks (Delta Lake, Spark, MLflow).

• Develop interactive dashboards and visual reporting layers in Tableau; translate findings into executive-ready narratives.

• Write production-quality Python scripts for data ingestion, transformation, automation, and model integration.

• Collaborate with data engineers, product managers, and business stakeholders to define KPIs and data requirements.

• Apply LLM-powered capabilities (e.g., SemiKong, GPT-4, Claude, Gemini, LLaMA, Mistral) to augment analytics workflows and automate insight generation.

• Conduct exploratory data analysis (EDA), statistical modelling, and root-cause analysis on large-scale datasets.

• Ensure data quality, governance, and lineage across analytical assets.

• Mentor junior analysts and contribute to the teams data literacy initiatives.

• Participate in cross-functional sprint planning and agile ceremonies as a technical SME.