Data Engineer

Data Engineer

Job ID: 42114

Experience: 5+ years

Must be a Veteran

Type: Contract / C2C Ok

Location: Bethlehem, PA

Must be a U.S. Military Veteran

No Agencies

Candidate should Provide technical expertise in needs identification, data modelling, data movement, translating business needs into technical solutions with adherence to established data guidelines and approaches from a business unit or project perspective. Good knowledge of conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL). Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively

· 5+ Years of experience as a Data Engineer

· Strong technical expertise in SQL is must

· Strong knowledge of joins and common table expressions (CTEs)

· Strong experience with Python

· Strong expertise in ETL process and with various data model concepts

· Knowledge of star schema and a snowflake schema

· Good to have knowledge on AWS services such as S3, Athena, Glue, EMR/Spark with major emphasis on S3 and Glue

· Experience with Big Data Tools and technologies

Key Skills:

· Good Understating of data structures and data analysis using SQL or Python

· Knowledge of implementing ETL/ELT for data solutions end to end

· Understanding requirements, and data solutions (ingest, storage, integration, processing)

· Knowledge of analyzing data using SQL

· Conducting End to End verification and validation for the entire application

Responsibilities:

· Understand and translate business needs into data models supporting long-term solutions.

· Perform reverse engineering of physical data models from databases and SQL scripts.

· Analyze data-related system integration challenges and propose appropriate solutions.

· Assist with and support setting the data architecture direction (including data movement approach, architecture / technology strategy, and any other data-related considerations to ensure business value)