Suyash Dhekale

Senior Data Engineer at Accenture (2024-02 – Present)

Automated data ingestion pipelines using Python to extract Excel files from SharePoint, transform data, and load it into Azure Data Lake Storage (ADLS); integrated multiple datasets from Microsoft Dataverse through secure connections for downstream processing.
Built scalable data processing pipelines in Databricks using PySpark to harmonize and standardize datasets from SharePoint and Dataverse, ensuring schema consistency and delivering high-quality unified data for analytics.
Designed and orchestrated Databricks Workflows to automate the creation of curated tables and views while configuring compute clusters to optimize performance, reliability, and cost efficiency.
Implemented incremental (delta) data loading strategies in Databricks templates, reducing pipeline runtime and improving overall data processing efficiency.
Developed and optimized stored procedures in Google BigQuery, including recursive logic for hierarchical transformations, enhancing query performance and enabling efficient reporting and analytics.
Managed production pipeline scheduling in Automic, troubleshooting scheduling issues, collaborating with cross-functional teams to resolve data pipeline incidents, and supporting client ad-hoc requests through root cause analysis and stakeholder interaction.
Optimized a Databricks data pipeline by implementing incremental processing, reducing execution time from 10 hours to 10 minutes and improving overall system performance.

Data Analyst at Tech Mahindra (2022-05 – 2024-02)

Specialized in vehicle telematics data analysis using SQL Server, AWS, Python, and Excel to derive operational insights from large-scale vehicle datasets.
Designed and maintained scalable and reliable data pipelines, ensuring high standards for availability, performance, and maintainability across the data architecture.
Diagnosed and resolved SQL Server data pipeline issues, including debugging code, analysing system logs, accessing AWS EC2 instances via SSH (PuTTY), and troubleshooting configuration issues using EC2 user data.
Implemented a density-based clustering algorithm (DBSCAN) to analyse vehicle routes and identify driving patterns and route clusters.
Extracted and analysed Vehicle Duty Cycles (Highway, City, and mixed terrains) to support vehicle performance evaluation and engineering analysis.
Conducted Exploratory Data Analysis (EDA) and hypothesis testing using Python and data visualization techniques to identify patterns and relationships across multiple vehicle telemetry variables.

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