Binaya Sharma
Data Engineer · SunnyData
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Kathmandu, Nepal
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Contact
✉️ [email protected]
🔗 LinkedIn
💻 GitHub
🌐 sharmabinaya.com.np
Certifications
Databricks Certified Data Engineer Professional
May 2026 – May 2028
Databricks Certified Data Engineer Associate
Dec 2025 – Dec 2027
Claude Certified Architect - Foundations
Sep 2026 – Sep 2027
Domains
Healthcare & Life Sciences
Manufacturing & Automotive
Enterprise Finance & Reporting
Education
BSc (Hons) Computer Science
First Class Honours
University of Wolverhampton
Languages
English — ● ● ● ● ○
Nepali — ● ● ● ● ●
Profile
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✨
Databricks Certified Data Engineer Professional with nearly 4 years of experience designing and delivering data engineering solutions across healthcare and manufacturing domains. Experienced in developing scalable ETL/ELT pipelines and lakehouse architectures using Databricks, Apache Spark, Python, and SQL. Skilled in incremental data processing, Spark performance optimization, and enterprise data migrations, with additional experience in AWS, Terraform, and CI/CD automation. Strong background in technical leadership, stakeholder collaboration, and enterprise data platform delivery.
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Technical Skills
| Area |
Tools & Technologies |
| Cloud Platforms |
AWS (S3, Glue, Athena, Kinesis) · Azure (ADLS, Azure Databricks) |
| Data Platforms |
Databricks (Delta Lake, Unity Catalog, Structured Streaming) · Apache Spark · Apache Kafka |
| Programming |
Python (PySpark) · Scala · SQL · PL/SQL · Shell scripting |
| Databases |
Oracle · Snowflake |
| AWS Infrastructure & Networking |
VPC Networking · IAM · Security Groups · NAT/Internet Gateways · VPC Endpoints |
| DevOps & CI/CD |
Terraform · GitHub Actions · CI/CD Pipelines · Docker · Git · GitHub · Bitbucket |
| Data Engineering Tools |
ODI · dbt · Airbyte · DBeaver |
| Specializations |
Lakehouse architecture · ETL/ELT development · Data modeling · CDC · Streaming · Spark performance tuning |
| Leadership |
Team leadership · Stakeholder collaboration · Mentoring · Delivery coordination |
Work Experience
Data Engineer — SunnyData
Sep 2026 – Present
- Building data engineering solutions on Databricks and Apache Spark as part of client delivery teams.
- Contributing to data pipeline development and lakehouse architecture across client-facing consulting engagements.
- Applying SunnyData delivery standards, internal frameworks, and Databricks best practices across client engagements.
Data Engineer / Databricks Solutions Consultant — Ultra Tendency Nepal
Nov 2025 – Aug 2026
- Supported a global manufacturing client through a Databricks partner engagement, contributing to the migration of legacy cloud data warehouse and notebook-based workloads onto Azure Databricks.
- Worked on ingestion pipelines supporting the integration of around 18 SAP source systems into the Databricks Lakehouse, contributing to pipeline development and optimization as additional source systems were onboarded.
- Re-implemented business transformation logic from legacy warehouse SQL and Python/Pandas-based notebook processing into Scala Spark frameworks and PySpark workflows.
- Built analytical data models and optimized distributed Spark pipelines for growing data volumes, using Delta Change Data Feed for incremental processing and partial/full recompute strategies to manage runtime and cost.
- Contributed to internal proofs of concept and technical evaluations alongside client delivery work, collaborating with ingestion, transformation, infrastructure, and architecture teams on solution design, migration planning, and Databricks onboarding.
Software Engineer — Infinite Nepal (formerly Cotiviti Nepal)
May 2022 – Nov 2024 · Trainee: Mar 2022 – May 2022
- Designed and maintained end-to-end ETL pipelines for large-scale US healthcare analytics platforms using Oracle SQL, PL/SQL, ODI, and in-house data integration frameworks.
- Improved the performance of PL/SQL packages, stored procedures, and ETL queries across multiple enterprise client accounts, reducing several long-running workloads by roughly 40–70%.
- Migrated client data integration workflows from legacy ODI implementations to internal ETL frameworks, improving scalability and operational efficiency.
- Built automation scripts for recurring data-processing and operational activities, reducing multi-day tasks to a few hours while supporting UAT, deployment, production issue resolution, integrations, and reporting deliveries.
- Led a team of 6–7 software engineers across ETL pipeline development, delivery coordination, and process improvement initiatives, improving delivery and SLA performance for a key enterprise client.