AWS Data Engineer

Job Description

We are looking for an AWS Data with primary skills on PySpark development who will be able to design and build solutions for one of our Fortune 500 Client programs, which aims towards building an Enterprise Data Lake on AWS Cloud platform, build Data pipelines by developing several AWS Data Integration, Engineering & Analytics resources. There is no requirement for Machine Learning skills. This is a high visibility, fast-paced key initiative will integrate data across internal and external sources, provide analytical insights, and integrate with the customer's critical systems.

Key Responsibilities

Design, build and unit test applications on Spark framework on Python.

Build Python and PySpark based applications based on data in both Relational databases (e.g. Oracle), NoSQL databases (e.g. DynamoDB, MongoDB) and filesystems (e.g. S3, HDFS)

Build AWS Lambda functions on Python runtime leveraging pandas, json, boto3, requests, avro libraries

Build PySpark based data pipeline jobs on AWS Glue ETL requiring in-depth knowledge on AWS Glue Dynamic Frames and Options

Build Python based event-driven integration with Kafka Topics, leveraging Confluent Kafka libraries

Design and Build Generic, Reusable utility applications in Python

Build the Python programs across Glue ETL jobs and Lambda functions

Optimize performance for data access requirements by choosing the appropriate native Hadoop file formats (Avro, Parquet, ORC etc) and compression codec respectively.

Design & Build S3 buckets, tiers, lifecycle policies, as strategic storage layer for Data Lake

Optimize performance of Spark applications in Hadoop using configurations around Spark Context, Spark-SQL, Data Frame, and Pair RDD's

Setup the Glue crawlers in order to catalog OracleDB tables, MongoDB collections and S3 objects

Configure Athena tables and SQL views based on Glue Cataloged datasets

Ability to monitor, troubleshoot and debug failures using AWS CloudWatch and Datadog

Ability to solve complex data-driven scenarios and triage towards defects and production issues

Participate in code release and production deployment.