Software Engineer Data Platform

Position Summary

The Software Engineer will assist in designing, developing, and deploying as part of a strategic modernization effort. The candidate will join a team of Engineers who will be responsible for optimizing and transforming our data architecture, infrastructure, operations, and related functions.This team will work with developers, architects, business / data analysts and data scientists on data initiatives and will ensure optimal data solutions.

Essential Job Functions:

• Leverage modern data management toolsets and coding methods to design, build, implement, and optimize data solutions of all types including support for OLTP and API/Microservices, data warehouses, data lakes, ODS, streaming data, analytic and BI/visualizations, etc.

• Transform legacy data structures and processes to modern, capable, and secure solutions in a hybrid cloud setup

• Apply Data Engineering & Design best practices to architect solutions, using a deep understanding of various data formats and database design approaches

• Design and Implement Data Services (DaaS) for consumption and various manipulations throughout the Data Ecosystem applying the contract first design principle and including use of API, Microservices, Microbatch, ELT Pipeline and other methods.

• Build best-practice driven data ingestion, develop tooling for increasing scale, accuracy, and automation in data pipeline, to integrate with decisioning, AI/NLP and consuming systems

• Ensure data security by designing controls and protection strategies

• Enable application performance and modernization by creating appropriate data capabilities to match

• Identify bottlenecks and issues and provide solutions to mitigate and address these issues.

• Makes a habit of covering most of their code with unit tests.

• Estimate efforts and ensure that work is completed on time.

• Responsible for code reviews and merges.

Position Requirements:

• Strong Experience Coding with Java, JavaScript (Nodejs), Python.

• Strong Knowledge of Design Patterns for Software and Data Engineering.

• Experience in on-prem and hybrid cloud infrastructure, including service and cost optimization

• Experience with production and analytics data, batch, and real time / streaming, etc.

• Experience with RDBMS (E.g., Oracle, SQL) as well as modern relational and unstructured data sources (like NoSQL), including cloud services (AWS/Google Cloud Platform/Azure).Hands on experience using tools is strongly preferred

• Knowledge of tools (or similar) such as Hadoop Stack, Airflow, Kafka, NiFi, PostgreSQL, Oracle, SQL Server, Elastic Search (ELK), JSON, Parquet, Avro and other Data Storage formats, Tableau, Superset and other Visualization Tools, Apache Atlas, and other Data-centric Apache Packages