TempD User
@tempduser
Senior cloud data engineer building cost-efficient AWS/Azure lakehouses, ETL/ELT pipelines, and trusted analytics at 99%+ SLA.
United StatesWhat I'm looking for
I’m a Cloud Data Engineer with 5+ years designing and optimizing large-scale data platforms across AWS and Azure. I build Lakehouse architectures, ETL/ELT pipelines, and dimensional models that support 100+ analytics users with 99%+ SLA reliability. I’m especially focused on Spark optimization, data quality frameworks, and cost-efficient cloud infrastructure.
At Analog Devices, I designed and optimized 40+ ETL/ELT pipelines using Python, PySpark, Glue, and EMR to process ~3TB/day of manufacturing and ERP data—reducing runtime by 30% while meeting 99.5% SLA targets. I productionized a Databricks Lakehouse (Bronze/Silver/Gold) with Delta tables across 15+ ingestion sources, implemented automated data quality using Great Expectations (cutting defects 40%+), and tuned Spark/EMR to lower AWS compute costs by 15%. I also strengthened governance with fine-grained RBAC/IAM for PII, and built masking/encryption pipelines to support GDPR/ISO 27001.
Before that, at Mphasis, I built 30+ Azure Data Factory pipelines into Synapse and ADLS, improving ETL processing time by 25% and enabling CDC/incremental ingestion to move data freshness from daily to hourly. Earlier roles—including DataAnalyst / Junior Data Engineer at 3i Infotech and an internship at Datamatics—shaped my focus on repeatable automation, validation, and clear business-aligned analytics.
Experience
Work history, roles, and key accomplishments
Designed and optimized 40+ ETL/ELT pipelines processing ~3TB/day across S3, Redshift, and Snowflake, reducing runtimes by 30% while meeting 99.5% SLA targets. Built a Databricks Lakehouse (Bronze/Silver/Gold) and implemented data quality, Spark tuning, and RBAC to cut production defects by 40%+ and AWS compute costs by 15%.
Data Engineer
Mphasis
Jan 2021 - May 2023 (2 years 4 months)
Built and maintained 30+ Azure Data Factory pipelines ingesting financial and customer datasets into Synapse and ADLS, reducing ETL processing time by 25% via SQL/query plan optimization. Implemented CDC and incremental ingestion (daily to hourly freshness) and improved release cycles from 2 weeks to 2 days using Azure DevOps CI/CD.
Data Analyst / Junior Data Engineer
3i Infotech
Jun 2019 - Dec 2020 (1 year 6 months)
Automated recurring reporting workflows with SQL and Python, eliminating 35–40% of manual Excel-based effort for monthly operational reports. Built ETL into SQL Server tables, standardized logic with reusable views/CTEs/stored procedures (dashboard refresh -25%), and improved monthly reporting accuracy by 20%+.
Developed and tested ETL workflows with SQL and Python for financial data systems, including data profiling and data quality rule creation under senior supervision. Supported Spark and Hadoop batch job monitoring/troubleshooting and built reusable validation scripts to reduce ETL testing cycles by 15–20%.
Education
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TempD hasn't added their education
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Tech stack
Software and tools used professionally
Availability
Location
United StatesAuthorized to work in
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