Akshay Pare

Senior Data Engineer with 6.5 years of experience designing scalable data platforms, distributed ETL pipelines, and analytics systems processing millions to billions of records. Experienced in building cloud-native data architectures using AWS, enabling organizations to transform large-scale raw data into actionable insights. Specialized in data warehousing, distributed data processing, and analytics engineering supporting large-scale enterprise analytics systems.

Senior Software Engineer at Motivity Labs (2025-05 – Present)

Working with operations teams supporting analytics for Google 3PDC (Third-Party Data Centers). Responsible for building analytics datasets, data models, and dashboards to monitor infrastructure performance and machine telemetry data.

• Built infrastructure analytics dashboards analyzing billions of machine telemetry records from third-party data centers.
• Designed scalable data models and transformations using BigQuery for processing large-scale operational datasets.
• Developed interactive Looker dashboards enabling stakeholders to monitor machine utilization, infrastructure performance, and operational metrics.
• Built analytics workflows that convert large-scale infrastructure data into actionable insights for operations teams.
• Collaborated with cross-functional teams to translate operational requirements into scalable analytics solutions.

Senior Data Engineer at Infocenter (2023-04 – 2025-04)

Led development of scalable enterprise data platforms and analytics pipelines supporting BI reporting and advanced analytics. Client: Glew.io

• Designed distributed ETL pipelines using AWS Glue and PySpark processing hundreds of millions of records across transactional and marketing datasets.
• Architected scalable AWS S3 data lake solutions storing GB-scale datasets optimized for analytics workloads.
• Developed Amazon Redshift data warehouse architectures supporting enterprise BI and analytics systems.
• Implemented scalable data models using star and snowflake schemas for high-performance analytical queries.
• Built automated data ingestion and transformation pipelines integrating multiple business data sources.
• Optimized SQL queries and data partitioning strategies improving analytics performance and reducing processing time.
• Developed Looker semantic models using LookML to enable self-service analytics for business teams.
• Built executive dashboards and KPI reporting systems using Looker for business performance monitoring.

Data Engineer at Infocenter (2020-04 – 2023-03)

Built large-scale ETL pipelines and analytics datasets for e-commerce and marketing analytics platforms. Client: Glew.io

• Developed data pipelines ingesting data from Shopify, Magento, WooCommerce, Google Analytics, Klaviyo, and Meta Ads.
• Designed transformation workflows using Python, SQL, and AWS Glue to unify customer, marketing, and sales datasets.
• Processed millions of daily transactional and behavioral events for analytics and reporting.
• Built scalable data lake architecture on AWS S3 for structured and semi-structured data ingestion.
• Implemented automated workflows for data ingestion, validation, and transformation.
• Improved reporting performance through optimized SQL queries and partitioned datasets.

Data Engineer Intern at Infocenter (2019-12 – 2020-03)

Supported development of ETL pipelines and analytics datasets. Client: Glew.io

• Assisted in building ETL pipelines using Python and SQL.
• Performed data validation, transformation, and quality checks.
• Supported development of datasets used in BI dashboards and reporting systems.

Bachelor of Engineering in Computer Science – VIT Bhopal (2014-09 – 2018-05)