Headline

Immediate Joiner | Infosys | Ex-Wipro | Data Engineer | PySpark · Databricks · Delta Lake | ETL/ELT Pipelines | Rest API | Azure ADLS · AWS S3 | Power BI · Tableau | Claude | AWS Certified | 3+ YOE | Dashboard BI Analyst

About

As a Data Engineer, I work on transforming raw data into actionable insights that support business decision-making. I design and develop interactive dashboards using Power BI, enabling stakeholders to monitor key performance indicators and identify trends efficiently. By implementing ETL processes using SQL and Power Query, I streamlined data preparation workflows, reducing manual effort and improving data accuracy. Build the pipelines that power decisions — and care deeply about getting every byte right. With 3+ years of hands-on experience in data engineering, I specialize in designing and delivering end-to-end ETL/ELT pipelines on Databricks, transforming raw data into reliable, analytics-ready assets across Bronze, Silver, and Gold layers. Currently at Infosys, I work with PySpark, Delta Lake, and Databricks Workflows to process large-scale datasets on Azure ADLS Gen2 and AWS S3. Ensuring 100% error-free pipeline execution, every release cycle. Before Infosys, I spent two years at Wipro building and maintaining data pipelines across heterogeneous systems. Writing complex SQL (MySQL, MSSQL), automating reporting workflows with Python (Pandas, NumPy), and partnering with business stakeholders to translate requirements into data-driven insights. I've always believed that good data engineering is invisible: when it works, the business just moves faster. Through optimized SQL queries and well-structured data models, I have improved report performance and ensured reliable, scalable data solutions that support ongoing business growth.

Location

Pune District

AI stack

claude

github copilot

openai

claudecode

ChatGPT

Julius AI

Work experience

Data Engineer at Infosys, Jun 2025 - Present · 1 yr 5 mos, Designing and maintaining end-to-end ETL/ELT data pipelines on Databricks, processing large-scale datasets across Bronze, Silver, and Gold medallion layers using PySpark and Delta Lake. - Achieved 100% error-free pipeline execution across all release cycles through rigorous schema validation, data reconciliation, and proactive monitoring. - Built and automated Dimension and Fact table transformations to support enterprise data warehousing and downstream analytical reporting. - Integrated Azure ADLS Gen2 and AWS S3 as primary cloud storage layers for ingestion, processing, and long-term retention at scale. - Automated workflow orchestration via Databricks Jobs and Workflows, significantly reducing manual operational overhead. - Published and maintained Power BI and Tableau dashboards on a monthly release cadence, improving stakeholder reporting efficiency by ~30%. -Conducted root cause analysis (RCA) for recurring pipeline failures, implementing permanent fixes that measurably improved platform stability and CSAT scores. - What I bring to the table: - Medallion architecture (Bronze, Silver, Gold) on Databricks - PySpark, Spark SQL, Delta Lake, Unity Catalog, Auto Loader - Dimension & Fact table transformations | Star schema DWH design - Orchestration via Databricks Jobs & Lakeflow Declarative Pipelines - BI dashboards in Power BI & Tableau with measurable reporting impact - AWS Certified Cloud Practitioner + Solutions Architect – Associate Beyond the stack

Data Analyst/ Engineer - Domain Expert at Wipro, Sep 2022 - May 2025 · 2 yrs 9 mos, Pune District, Maharashtra, India, - Delivered data engineering and analytics solutions across heterogeneous systems, building ETL pipelines, SQL-driven reporting workflows, and Python automation to support business intelligence operations. - Developed and maintained data pipelines on Databricks with zero data loss — validating schemas, reconciling records, and ensuring consistent data formats across source and target environments. - Reduced query processing time by ~40% and improved overall query performance by ~25% through SQL optimisation, stored procedures, and targeted refactoring of recurring data tasks. - Automated data extraction, transformation, and reporting workflows by integrating Python (Pandas, NumPy) with SQL, significantly cutting manual effort across the team. - Analysed large datasets using SQL and Databricks to surface actionable business insights, partnering directly with stakeholders to define and refine reporting requirements. - Maintained incident runbooks, SOPs, and operational documentation; performed log analysis and job recovery to minimise pipeline downtime.

Education

Master of Computer Applications, Computer Engineering, CHANDIGARH UNIVERSITY

Bachelor of Computer Applications, Computer Programming, Specific Applications, Panjab university

Public links

github: https://github.com/mohittaneja786

insight-forge-studio-03.lovable.app: https://insight-forge-studio-03.lovable.app/