Lead Big Data Engineer

Role Objective:

Big Data Engineer will be responsible for expanding and optimizing our data and database architecture, as well as optimizing data

flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who

enjoys optimizing data systems and building. The Data Engineer will support our software developers, database architects, data

analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing

projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products

Roles & Responsibilities:

1.Strong SQL Skills: Candidate should be proficient in writing and executing complex SQL queries (no PL/SQL) and be able

to handle real-world scenarios confidently.

2. Hands-on Functional Programming (Scala): Strong hands-on experience in Scala is essential.

Solid Data Engineering Fundamentals: Emphasis is on strong foundational understanding rather than tool-specific

expertise.

3.Experience in Data Quality & Optimization: Candidate should have a sound understanding of data quality practices,

performance optimization techniques, and solution design in both event-driven and batch processing contexts including

data modeling.

4.Sound knowledge in Spark architecture and distributed computing and Spark streaming, including RDD and Data frames

core functions, troubleshooting and performance tuning.

5.Experience in analyzing, re-architecting, and re-platforming on-premises data warehouses to data platforms on any cloud

(AWS is preferred)

6. Experience in any cloud (ETL/ELT pipelines, Datalake and Data streaming) is preferred.

7. Understand the client requirement and able to design, develop from scratch and deliver.

8.. Able to mentor new members for onboarding to the project.

EXPERTISE AND QUALIFICATIONS

Experience: 5 to 9 years

Must have Skills:

• Scala/Java/React
• Spark
• SQL
• Python
• Any cloud (AWS preferable)
• Kafka /Kinesis/Any streaming services
• Hive, ETL/ELT design experience
• • CI/CD experience (ETL pipeline deployment)
• • Data Modeling experience
• • Data Warehouse experience (Snowflake)
• Good to Have Skills:
• • Git/similar version control tool
• • Knowledge in Microservices
• • Airflow or similar tools