Aws Data Engineer

Platform & Expectations

• The enterprise-level data platform already exists.
• Role involves enhancement and building on top of it.
• Candidates should be ready to work on various data solutions, not just ADP.

Experience Requirement

• 5-6 years total experience preferred.
• Minimum 3-4 years as an AWS Data Engineer.
• For 8+ years total experience, 56 years in AWS data engineering is expected.

Must-Have Skills

• AWS Services: S3, Lambda, Glue, Redshift, SNS, Step Functions, DataBrew.
• Python and Spark: Strong proficiency required.
• Data warehousing, lakehouses, ETL/data pipelines.
• Full-stack data engineering capabilities.
• Basic DevOps and automation experience.

Soft Skills

• Strong communication (multi-stakeholder role).
• Ownership and accountability in tasks.

Other Notes

• CloudFormation is a good-to-have, not mandatory.

Role Overview

• The person will be part of the EDP Data Platform (EDP) team for a major insurance client. Will work with different stakeholders for architecting and building EDP application platform to support clients' internal data teams to onboard and provision data in Data Cloud.
• This application would be architected using Micro Services Architecture to support different workloads like Data marts, Data warehouse, AI/ML.
• The person will also be required to participate actively in brainstorming sessions for improvement opportunities and take it to completion.
• A suitable candidate should have 4+ years of experience in developing enterprise-level applications and should possess a go-getter attitude. Should be able to deal with ambiguity.
• Experience in life insurance preferred but not mandatory.

Key Responsibilities & Skillsets

• Common Skillsets:
• Superior analytical and problem-solving skills.
• Should be able to work on a problem independently and prepare client-ready deliverables with minimal or no supervision.
• Good communication skill for client interaction.
• Application Development Skillsets:
• Experience in designing, implementation, and testing of Python applications with understanding of object-oriented programming, multi-tier architecture, parallel/multi-threaded programming.
• Programming experience with Python is a must; Java/Scala is nice to have.
• Experience with AWS technologies including AppSync, Lambda, Step Functions, Event Bridge.
• Solid experience of AWS services such as CloudFormation, S3, Glue, EMR/Spark, RDS, DynamoDB, Lambda, Step Functions, IAM, KMS, SM, etc.
• Knowledge of modern cloud-native data warehouses, e.g., AWS Redshift, Snowflake, or Azure Synapse Analytics.
• Experience implementing metadata solutions leveraging AWS non-relational data solutions such as ElastiCache and DynamoDB.
• Working experience with Python and Spark is desired. Experience working on Agile projects.
• AWS Solutions Architect or AWS Big Data Certification preferred.
• Ability to thrive in a high energy, high growth, fast-paced, entrepreneurial environment. Willing to learn new skills and implement new technologies.
• Strong organizational, written and verbal communication skills with high attention to detail and able to work independently with minimal supervision.
• Highly-collaborative team player who can build strong relationships at all levels of the technology and business organization.

Candidate Profile

• Bachelors/Master's degree in computer science/engineering, operations research or related analytics areas welcome to apply.
• 4+ years experience in enterprise application development, preferably in Life Insurance but not mandatory.
• Application development experience.
• Team Management.
• Superior analytical and problem-solving skills.
• Outstanding written and verbal communication skills.
• Able to work in a fast-paced, continuously evolving environment and ready to take up uphill challenges.
• Is able to understand cross-cultural differences and can work with clients across the globe.