Full Stack Python Developer (FSPD)

Job role : Full Stack Engineer (Python)

Location : Nashville, TN (Onsite)

Duration : 6 months+

MUST HAVES :

5+ yrs of Experience with AWS capabilities; Glue, DynamoDB, Lambda, Redshift, elastic search on large scale / enterprise level deployments

5+ yrs of experience with API and Strong knowledge of Data Integration (e.g. Streaming, Batch, Error and Replay)

5+ yrs of experience with Python, PySpark and Apache Spark

Job Summary :

The objective of this position is to work with business and technical experts to implement software engineering best practices related that promotes the highest re usability across the US and Global.

The individual must have superb analytical and technical skills coupled with the ability to drive project deliverables.

The individual will be expected to participate in the collaborative concept definition, architectural refinement, software design and realization of products that support the strategic technology needs to support the organization.

A full stack engineer is a person that has a breadth of knowledge in computer science, a problem-solving mentality and a desire to learn.

This person is comfortable working within a technical capacity across many of the sectors including core development on platform, data processing and report generation.

The Full stack Engineer will be working in a team that demands technical excellence and whose members are expected to hold each other accountable in the overall success of the output.

Focus for this team is on the delivery of innovative solutions to complex problems.

Skills :

Software development experience with Python, PySpark and Apache Spark

Proficiency in SQL, relational and non-relational databases, query optimization and data modelling.

Strong knowledge of Data Integration (e.g. Streaming, Batch, Error and Replay) and data analysis techniques.

Experience with GitHub, Jenkins, and Terraform.

Experience with Teradata (Vantage) or any RDBMS system / ETL Tools

Good experience on designing and developing data pipelines for data ingestion and transformation using Spark.

Excellent in trouble shooting the performance and data skew issues.

Working knowledge on the implementation of data lake ETL using AWS glue, Databricks etc.

Experience with large scale distributed relational and NoSQL database systems.

Excellent communication skills

Provide recommendations and design optimal configurations for large-scale deployments.