Big Data Engineer

Affine Analytics; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Affine Analytics is seeking a Big Data Engineer to expand and optimize data and database architecture, and to streamline data flow for cross-functional teams. You will build scalable pipelines and wrangle large datasets to support analytics and product initiatives.

The role requires hands-on Scala, Spark, SQL and AWS experience, with the ability to mentor newer teammates and guide data platform design across on-prem and cloud environments.

Qualifications

• Proficient in Scala, Spark and SQL with hands-on experience.
• Strong understanding of data quality, performance optimization and data modeling.
• Experience with cloud data platforms (AWS) and streaming architectures.

Responsibilities

• Build and optimize data and database architecture for cross-functional teams.
• Develop and maintain data pipelines and real-time/batch processing.
• Mentor new team members and guide data platform design.
• Collaborate with software engineers, DBAs, data analysts and data scientists.

Skills

Scala

Spark

SQL

AWS

Kafka

Kinesis

Streaming

Hive

ETL/ELT design

CI/CD

Data Modeling

Job description

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

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.
3. Solid Data Engineering Fundamentals: Emphasis is on strong foundational understanding rather than tool-specific expertise.
4. 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 contextsincluding data modeling.
5. Sound knowledge in Spark architecture and distributed computing and Spark streaming, including RDD and Data frames core functions, troubleshooting and performance tuning.
6. Experience in analyzing, re-architecting, and re-platforming on-premises data warehouses to data platforms on any cloud (AWS is preferred)
7. Experience in any cloud (ETL/ELT pipelines, Datalake and Data streaming) is preferred.
8. Understand the client requirement and able to design, develop from scratch and deliver.
9. Able to mentor new members for onboarding to the project.

Must have Skills:

• Scala
• Spark
• SQL
• AWS
• Kafka /Kinesis/Any streaming services
• Hive, ETL/ELT design experience
• CI/CD experience (ETL pipeline deployment)
• Data Modeling experience