Pyspark Developer

TSR, Inc

Tampa, FL, United States

2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

dice.com

Tech stack

Third Normal Form BigQuery Databases Directed Acyclic Graph (Directed Graphs) Data Architecture Extract Transform Load (ETL) Data Structures Data Systems Data Vault Modeling Data Warehousing Relational Databases Software Design Patterns

+14 more

Distributed Systems Memory Management Apache Hadoop Apache Hive Python (Programming Language) PostgreSQL Oracle (Applications) SQL Databases Snowflake Apache Spark Pyspark Optimization Algorithms Star Schema Data Pipelines

Requirements

PySpark Mastery: Production-level expertise in Apache Spark using Python (PySpark)
Must understand Spark internals (DAGs, shuffling, memory management, and optimization techniques)
Data Modeling: Proven track record of building complex data models from scratch (Star/Snowflake schemas, Data Vault, or 3NF)
Database & SQL: Expert-level proficiency in SQL
Extensive hands-on experience with massive relational databases (e.g., Oracle, PostgreSQL) and modern data warehouses/lakes (e.g., Snowflake, BigQuery, or Hive/Hadoop)
Systems Design: Clear understanding of distributed systems processing, ETL/ELT design patterns, and enterprise data warehousing principles
Communication: Demonstrated ability to translate complex technical concepts into clear, concise language for non-technical stakeholders and business leaders
We are seeking a highly experienced PySpark Developer to lead the design, architecture, and development of mission-critical data pipelines and enterprise data models
As a senior technical leader, you will bridge the gap between complex business requirements and highly scalable data architecture
The ideal candidate possesses deep expertise in PySpark, advanced SQL optimization, and enterprise data modeling
You will not only be a hands-on technical contributor but also serve as an architectural guide, mentoring junior developers, establishing best practices, and ensuring that data solutions are highly performant, resilient, and aligned with Client
Lead the transition from legacy data structures to modern, scalable cloud/hybrid