Certified Snowflake consultant with strong experience in designing and delivering scalable ETL/ELT pipelines, automated data workflows, and cloud-based analytics platforms. Proficient in Python, Databricks (Spark/PySpark…
Certified Snowflake consultant with strong experience in designing and delivering scalable ETL/ELT pipelines, automated data workflows, and cloud-based analytics platforms. Proficient in Python, Databricks (Spark/PySpark), Snowflake, and REST API integrations, with a proven ability to collaborate effectively within agile, cross-functional teams.
<p>Designed and delivered analytics pipelines across Application Processing and Payments domains using AWS, Azure, Databricks, and Snowflake, integrating data from multiple upstream systems into trusted, analytics-ready datasets.</p><p> Built and maintained dbt-driven transformation layers (RAW → STG → SILVER → GOLD) with modular models, reusable macros, automated tests, and documentation.</p><p> Developed and optimised Databricks (Spark/PySpark) jobs for upstream data ingestion, enrichment, and validation prior to analytics modelling.</p><p> Orchestrated end-to-end workflows with Apache Airflow, managing cross-platform dependencies, scheduling, retries, and operational monitoring across Databricks and Snowflake.</p><p> Implemented robust data quality and governance controls, including schema enforcement, business rule validation, deduplication, and late-arriving data reconciliation.</p><p> Integrated Snowflake Cortex AI with streamlit to summarise unstructured free-text data into concise, actionable insights for improved decision-making and compliance reporting.</p><p> Partnered with product owners, business analysts, and data consumers to translate business requirements into scalable, analytics-ready data models.</p><p> Delivered a scalable Application Lifecycle analytics platform across AWS, Databricks, and Snowflake, providing trusted, analytics-ready data for application status, SLA, and payment reporting.</p><p> Developed a Snowflake GenAI prototype using Cortex Analyst, Cortex Code, Semantic Models, Cortex AI, and Streamlit, enabling natural-language data analysis, AI-assisted SQL generation, and summarisation of unstructured data to demonstrate GenAI-driven business insights.</p>
<p>Performed exploratory data analysis and statistical modelling using SAS and SQL, identifying data quality issues and implementing validation protocols to ensure accuracy.<br>
Collaborated with cross-functional teams to translate business requirements into analytical solutions and deliver actionable insights.</p>
<p>Built SAS-based data pipelines to Azure Databricks, rewriting complex SAS logic into scalable PySpark workflows.</p><p> Designed and implemented secure, automated ingestion of raw datasets from Oracle into Azure Data Lake (ADLS) using Databricks.</p><p> Performed comprehensive data validation including schema enforcement, record reconciliation, duplicate detection, and data quality checks using PySpark.</p><p> Re-engineered statistical and business transformation logic from SAS into distributed Spark-based processing for standardized datasets.</p><p> Built and optimized Delta Lake tables to support ACID transactions, incremental processing, and efficient data storage.</p><p> Developed end-to-end medallion architecture (RAW → BRONZE → SILVER → GOLD) within Databricks for scalable data transformations.</p><p> Implemented incremental data processing using Spark, Delta Lake, and partitioning strategies for high-performance pipelines.</p><p> Automated ELT workflows and orchestration using Databricks jobs and integrated pipelines with Snowflake for downstream analytics.</p>
<p>Reviewed business requirements and technical specifications to ensure testability, completeness, and alignment with data processing rules.</p><p> Extracted data from relational databases into SAS, applying data quality checks, transformations, and edit rules based on transfer specifications.</p><p> Developed complex SAS Macros to automate repetitive processes, improve efficiency, and support unit testing and reconciliation activities.</p><p> Performed multi-system data validation, reconciliation, and defect analysis, working with stakeholders to resolve issues and conduct root cause analysis.</p>
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