About Jayrajsinh
I am Jayrajsinh Zala, a Data Engineer with 3+ years of experience designing and delivering scalable, cloud-native data platforms across Microsoft Azure and AWS. I specialise in Azure Databricks, Azure Data Factory, Apache Spark, Delta Lake, and Medallion Lakehouse architecture — building high-performance ETL/ELT pipelines that are reliable, governed, and built to scale.
I am currently at the Environment Agency (UK Government), leading a complex multi-region water data migration programme and delivering a public-facing environmental permit registry — engineering with real public impact in a regulated environment where data accuracy and governance are critical.
Previously at Quantix IT, I delivered a cloud-native data platform serving 2,000+ daily users, reduced processing costs by 30%, cut data defects by 45%, and compressed release cycles by 50% through CI/CD automation.
I bring strong expertise in data governance (Microsoft Purview, Unity Catalog, RBAC), data quality frameworks, infrastructure-as-code (Terraform), and streaming pipelines (Kafka, Event Hubs). I hold a Master's in Data Science from Coventry University and three Databricks certifications.
I work closely with stakeholders at all levels, translating business needs into scalable technical solutions — and I take full ownership of outcomes.
English
Native or bilingual
Hindi
Native or bilingual
Gujarati
Native or bilingual
Remote only
Primarily works remotely
Experience
- Environment AgencyData EngineerMay 2026 - Today (2 months)Birmingham, UK
- Leading end-to-end migration of multi-region water datasets into a centralised data platform, coordinating with regional stakeholders to align data standards and resolve legacy schema inconsistencies
- Designing and implementing ETL/ELT pipelines to process and standardise environmental monitoring data at scale
- Driving the delivery of a public permit registry, improving transparency and public access to environmental licensing data
- Collaborating with cross-functional teams including environmental scientists, policy leads, and software engineers to define data requirements and ensure regulatory compliance
- Applying best practices in data governance, data quality, and security to meet government standards
- Quantix ITData EngineerJuly 2023 - Today (3 years)Coventry, UK
- Built and maintained scalable data infrastructure on 𝗔𝗪𝗦 (S3, Glue, Redshift) and 𝗔𝘇𝘂𝗿𝗲 (Data Factory, Databricks, Synapse) to support high‑volume ingestion, transformation, and ML workloads.
- Developed and automated ETL/ELT pipelines using 𝗣𝘆𝘁𝗵𝗼𝗻, 𝗦𝗤𝗟, and 𝗣𝘆𝗦𝗽𝗮𝗿𝗸 across APIs, databases, and streaming data, reducing manual effort by 60%.
- Optimized big data pipelines handling billions of records through partitioning, compression, and Spark tuning, improving performance by 45% and ensuring 98% data accuracy with robust quality frameworks.
- Enabled real‑time and batch analytics via 𝗞𝗮𝗳𝗸𝗮 and API integrations in AWS and Databricks, powering near real‑time insights and data‑driven decision‑making.
- Designed data models and transformations using dimensional and medallion architectures, increasing ML‑readiness and data discoverability for analytics teams.
- Implemented orchestration and monitoring with 𝗔𝗽𝗮𝗰𝗵𝗲 𝗔𝗶𝗿𝗳𝗹𝗼𝘄, 𝗗𝗕𝗧, and 𝗔𝗪𝗦 𝗦𝘁𝗲𝗽 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀, enhancing reliability and reducing pipeline downtime by 30%.
- Delivered analytics‑ready datasets integrated with 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 and 𝗧𝗮𝗯𝗹𝗲𝗮𝘂, accelerating reporting cycles and improving visibility into key business KPIs.
- Engineered and supported a 𝗟𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲 architecture using 𝗗𝗲𝗹𝘁𝗮 𝗟𝗮𝗸𝗲, reducing data silos by 70% and enabling seamless analytics across teams.
- Strengthened data governance and cataloging using 𝗔𝗪𝗦 𝗚𝗹𝘂𝗲 and 𝗔𝘇𝘂𝗿𝗲 𝗣𝘂𝗿𝘃𝗶𝗲𝘄, ensuring compliance, traceable data lineage, and easier data discovery.
- Optimized cloud infrastructure with auto‑scaling, cost tuning, and monitoring, achieving up to 25% savings while maintaining high performance.
- Collaborated cross‑functionally with product, analytics, and ML teams to align pipelines with model training and experimentation, streamlining AI workflows and deployment cycles.
- Quantix ITData Engineer InternJanuary 2023 - June 2023 (5 months)Coventry, United Kingdom
- Supported the data engineering team in building ETL pipelines and visualization solutions on 𝗔𝘇𝘂𝗿𝗲, gaining hands‑on experience with Azure Data Factory, PySpark, and analytics workflows.
- Assisted in designing and implementing ETL pipelines using 𝗔𝘇𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗙𝗮𝗰𝘁𝗼𝗿𝘆 and 𝗣𝘆𝗦𝗽𝗮𝗿𝗸 to ingest and transform data from multiple sources for reporting and analytics.
- Performed data preprocessing and cleaning to improve reliability and consistency across dashboards and reports used by business teams.
- Created interactive 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 dashboards to visualize KPIs, helping stakeholders track performance and make data‑driven decisions.
- Collaborated with senior engineers to learn and apply data modeling concepts, 𝗗𝗲𝗹𝘁𝗮 𝗟𝗮𝗸𝗲 architectures, and 𝗔𝘇𝘂𝗿𝗲 𝗦𝘆𝗻𝗮𝗽𝘀𝗲 for scalable querying.
- Contributed to initial pipeline setups, including schema mapping, validation rules, and transformation logic under mentor guidance.
- Gained exposure to data governance, metadata management, and data quality checks to ensure accurate and compliant datasets.
- Experimented with basic 𝗣𝘆𝗦𝗽𝗮𝗿𝗸 optimizations for handling larger datasets, strengthening understanding of distributed processing.
- Documented workflows, data flows, and process improvements to support knowledge transfer and future automation.
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Education
- Master of Science - MSCoventry University2026Data Science And Computational Intelligence
- Bachelor's degreeGovernment Engineering College2024Computer Engineer