Lead Data Engineer - AWS

Job Description - Lead Data Engineer (AWS)

As a Lead Data Engineer, you will be playing a crucial role in leading a dynamic team of data engineers and being responsible for technical architecture, design, implementation, optimizing and maintenance of data engineering solution components for our customers. You will be required to have strong hands-on experience in implementing and leading technical architecture, design and delivery of data engineering solutions on AWS, with a good understanding of data warehouse and data lake architecture patterns.

Key Responsibilities:

1. Technical Architecture & Design:

- Lead technical architecture and design efforts for data engineering solution components for delivering business solutions

- Design and implement scalable, secure and resilient data engineering solutions on AWS, with a good understanding of data architecture patterns

- Evaluate and select appropriate technology stack for data engineering solution components - cloud native services, open-source tools, data storage, data processing frameworks etc.

2. Data Engineering Development:

- Lead, mentor and manage a team of dynamic data engineers for development, testing and implementation of data pipelines ensuing quality, performance and on-time delivery

- Responsible for detailed technical design and data mapping specification

- Ensure adherence to industry best practices, coding standards and guidelines driving continuous improvement in code quality and delivery excellence

- Optimize data solutions for performance, cost-efficiency and scalability

- Ensure data quality and integrity for downstream systems and applications

3. Technical Project Management:

- Plan, prioritize and manage data engineering projects, ensuring timely delivery with quality

- Identify and mitigate risks, troubleshoot issues, handle customer escalations

- Ensure alignment with business requirements and priorities, working closely with stakeholders - both internal and customer

4. Collaboration and Documentation:

- Maintain comprehensive technical documentation, including architecture diagrams, high level / low level data integration design, data mapping specifications, database design etc.

- Working closely with peers, BI engineers and data scientists to enable advanced analytics, machine learning models and reporting solutions

Requirements:

- 8+ years of hands-on experience in delivering data engineering solutions

- Experience leading a team of 5+ team members, responsible for technical project management including stakeholder management, design review, code reviews and mentoring

- Strong hands-on experience in AWS, with experience in data engineering related services and technologies including AWS Glue, Lambda, Amazon Redshift, EMR, Amazon Kinesis etc.

- Expertise in database concepts, SQL and relational modelling

- Good understanding and experience working with NoSQL databases

- Strong hands-on experience in implementing data pipelines using Python and PySpark

- Good understanding of data lake and data warehouse concepts, modern data architecture patterns and industry trends in data engineering space

- Hands-on experience in data modelling, with a good understanding of both ER modelling and dimensional modelling

- Good understanding and experience implementing data quality management solutions

- Good understanding of metadata management for data engineering solutions and data platforms

- Good understanding of data governance concepts - including data stewardship, data security and data privacy management

- Experience with version control tools like Git for managing version control for source code

- Experience with DevOps processes, including experience implementing CI/CD pipelines for data engineering solution components

- Strong analytical and problem-solving skills.

- Excellent communication and collaboration skills

Good to Have:

- Certifications on AWS platform, preferably related to Data Engineering

- Experience working with Amazon AppFlow, API Gateway, DynamoDB etc.

- Good understand and experience working with BI/visualization tools like PowerBI

Skills

Data Engineering, AWS, Python, PySpark, SQL, AWS Glue, Redshift