Published on May 5, 2025. Modified on May 13, 2025.
Position Title: AWS Technical Lead Data Engineer
Employment Type: Full time (work from office)
Location: Bangalore/ Hyderabad
Position Summary:
As an AWS Technical Lead Data Engineer, you will play a pivotal role in leading and mentoring data engineering teams, architecting and designing robust data solutions on AWS, and serving as the primary technical point of contact for clients. You will leverage your deep expertise in AWS cloud technologies, data engineering best practices, and leadership skills to drive successful project delivery and ensure client satisfaction.
Key Responsibilities:
Technical Leadership: Provide technical guidance and mentorship to data engineering teams, fostering a culture of innovation and continuous improvement.
Solution Architecture: Design and architect scalable, high-performance data solutions on AWS, leveraging services such as S3, Glue, Lambda, EMR, Redshift, Dynamo DB, Kinesis, and Athena to meet client requirements.
Client Engagement: Serve as the primary technical point of contact for clients, understanding their business needs, and translating them into effective data solutions.
Project Management: Lead and manage end-to-end project delivery, ensuring projects are completed on time, within budget, and to the highest quality standards.
Data Modeling: Develop and maintain comprehensive data models that support analytics, reporting, and machine learning use cases.
Performance Optimization: Continuously monitor and optimize data pipelines and systems to ensure optimal performance and cost-efficiency, utilizing tools like Cloud Watch and AWS Cost Explorer
Technology Evangelism: Stay abreast of the latest AWS technologies and industry trends, and advocate for their adoption within the organization.
Team Collaboration: Foster strong collaboration with data scientists, analysts, and other stakeholders to ensure alignment and successful project outcomes.
Technical Skills and Expertise:
AWS Services: Deep understanding of core AWS services for data engineering, including S3, Glue, Lambda, EMR, Redshift, Dynamo DB, Kinesis, Athena, Cloud Watch, and IAM.
Programming Languages: Proficiency in Python, SQL, and Py Spark for data processing, transformation, and analysis.
Data Warehousing and ETL: Expertise in designing and implementing data warehousing solutions, ETL processes, and data modeling techniques.
Infrastructure as Code (Ia C): Experience with tools like Cloud Formation or Terraform to automate and manage infrastructure provisioning.
Big Data Technologies: Familiarity with big data frameworks like Apache Spark and Hadoop for handling large-scale data processing.
Qualifications:
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
10+ years of experience in data engineering, with at least 3+ years in a technical leadership role.
Deep expertise in AWS cloud technologies and data services.
Proven track record in architecting and delivering complex data solutions on AWS.
Strong leadership, communication, and client-facing skills.
Experience in data modeling, ETL processes, and data warehousing.
Excellent problem-solving, analytical, and decision-making skills.
Qualifications:
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
10+ years of experience in data engineering, with at least 3+ years in a technical leadership role.
Deep expertise in AWS cloud technologies and data services.
Proven track record in architecting and delivering complex data solutions on AWS.
Strong leadership, communication, and client-facing skills.
Experience in data modeling, ETL processes, and data warehousing.
Excellent problem-solving, analytical, and decision-making skills.
