Ashish Machcha

Snowflake-focused Data Engineer with 4+ years of data experience, including 3+ in dedicated data engineering roles, building production ETL/ELT pipelines, cloud warehouses, and dimensional models on Snowflake and AWS. Strong expertise in building analytics-ready data models on Snowflake using Medallion (Bronze, Silver, Gold) architecture and incremental dbt models with automated testing and lineage. Proficient in distributed data processing with Apache Spark, PySpark, and Databricks, and in workflow orchestration with Apache Airflow including DAG design, dependency management, and failure recovery.

Hands-on with AWS data services (S3, Glue, Lambda, Redshift) and with dimensional modeling: star schema design, fact and dimension development, and data warehousing best practices. Strong in data quality engineering including schema validation, duplicate detection, referential integrity, and Great Expectations, delivered in Agile/Scrum, client-facing environments with clear documentation and stakeholder communication.

Data Engineer - Redux Solutions - Mumbai, India

(2022-08 - 2024-07)

• Built and maintained 10+ ETL/ELT pipelines processing 200GB+ of data daily across AWS and Snowflake, delivering analytics-ready datasets to business stakeholders.
• Designed Gold-layer star schema fact and dimension tables, reducing dashboard load times by 30% and saving stakeholders 10+ hours weekly of manual data aggregation.
• Developed 30+ incremental dbt models on Snowflake following Bronze, Silver, and Gold layers, with automated tests catching 90%+ of upstream schema drift before production.
• Built batch and near real-time ingestion into Snowflake using staged COPY loads from S3 and Apache Kafka streamed via Snowpipe Streaming, cutting end-to-end data latency from hourly batch loads to under 2 minutes.
• Orchestrated production pipelines in Apache Airflow with dependency management, retry logic, and failure alerting, resolving job failures and delayed loads within SLA.
• Implemented data quality and governance checks including schema validation, null handling, duplicate detection, and referential integrity enforcement.
• Partnered with client stakeholders to gather requirements, define KPI logic, and document source-to-target mappings.
• Tuned Snowflake warehouse sizing, table clustering, and query patterns on high-volume Gold-layer tables, lowering compute credit consumption and improving query response times for BI users.

Data Engineer - Clover Infotech - Mumbai, India

(2021-04 - 2022-07)

• Designed AWS ingestion pipelines with S3, Glue, and Lambda, replacing manual file drops with scheduled automated loads for downstream reporting.
• Developed Databricks PySpark transformations processing 50GB+ datasets for data cleansing, joins, aggregations, and validation across structured sources.
• Implemented Great Expectations and PySpark validation checks for null rates, row counts, duplicates, and schema conformance, reducing downstream data incidents by 40%.
• Monitored and debugged ingestion failures across production jobs, driving root cause analysis and resolving 95%+ of incidents within SLA across 4+ business dashboards.
• Modeled curated reporting tables from business requirements, feeding Tableau and Power BI dashboards used by business teams.

Data Analyst - Archy Infotech - Mumbai, India

(2019-10 - 2021-03)

• Translated business requirements into structured analytical solutions using Python and SQL.
• Performed exploratory data analysis to uncover trends, correlations, and key performance drivers.
• Built and maintained Tableau dashboards and automated Excel reports for stakeholder consumption.
• Automated recurring reporting tasks using Python scripts, reducing manual reporting effort.
• Participated in Agile ceremonies including sprint planning, reviews, and retrospectives.

Master of Science - Computer Science - Southern Illinois University, Carbondale (2024-08 - 2026-05)