Lead AWS Data Engineer

About The Role

As a Lead AWS Data Engineer, you will make an impact by designing, building, and optimizing scalable cloud-based data platforms and engineering solutions that enable data-driven business decisions. You will be a valued member of the Data Engineering team, working collaboratively with product owners, architects, business stakeholders, and engineering teams to deliver modern data solutions that support enterprise initiatives.

Responsibilities

• Design, build, and maintain scalable data pipelines using Databricks, Snowflake, AWS services, and DBT.
• Develop and optimize data ingestion frameworks, including serverless solutions using AWS Lambda and Step Functions.
• Build and support robust data models, schemas, and medallion architecture patterns to ensure high-quality, governed data assets.
• Lead technical design discussions, conduct code reviews, mentor engineers, and promote software engineering best practices across the team.
• Partner with product owners and business stakeholders to translate business requirements into scalable, secure, and cost-effective technical solutions.

Requirements

• Strong hands-on experience with Databricks, including building and orchestrating production-grade data pipelines.
• Extensive experience with AWS services, particularly Lambda, Step Functions, and cloud-native data processing solutions.
• Expertise in Snowflake and DBT for data transformation, modeling, and analytics enablement.
• Experience implementing medallion architecture, data warehousing solutions, and enterprise data governance standards.
• Experience supporting large-scale enterprise data modernization initiatives.
• Proven ability to source, integrate, and standardize data from multiple line-of-business applications using APIs, native connectors, and other ingestion methods.
• Experience designing and developing APIs, backend services, and scalable data architectures.
• Demonstrated leadership experience providing system design guidance, conducting code reviews, and mentoring engineering teams.
• Strong communication skills with the ability to translate business requirements into technical solutions.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience.
• Experience supporting large-scale enterprise data modernization initiatives.
• Expertise in performance tuning and cost optimization for cloud-based data platforms.
• Knowledge of DataOps, CI/CD practices, and infrastructure-as-code methodologies.
• Experience working in highly regulated industries such as insurance or financial services.
• Strong understanding of data governance, data quality frameworks, and master data management principles.

Skills

• Experience with Databricks, Snowflake, AWS services, and DBT.
• Leadership experience in technical design and mentoring.
• Strong communication and translation skills.
• Experience with APIs, native connectors, and data ingestion methods.
• Performance tuning and cost optimization expertise.
• Data governance, data quality, and master data management knowledge.

Benefits

• Cognizant Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Pay

The annual salary for this position is between $125,000 - $150,000 depending on experience and other qualifications of the successful candidate.

Schedule

This is a hybrid position requiring attendance at a client or Cognizant office in Hartford, CT. Based on the business requirements of the role, the working arrangements may change based on the project you're engaged in, as well as business and client requirements.