Job Title: Data Analyst IV (IAM AWS Data Lake)
Location Requirements: Hybrid
Job Type: Contract
Role Overview:
You will lead the design, architecture, and implementation of enterprise data solutions on AWS. This role combines technical leadership with architectural ownership. You will partner with data architects, data scientists, product owners, and business stakeholders to build scalable, secure, and reliable data platforms. You will mentor engineers, set engineering standards, and help shape the organization’s data modernization and AI-readiness roadmap.
Responsibilities:
- Lead the design, architecture, and implementation of enterprise data engineering solutions across the AWS ecosystem
- Collaborate with lead developers, data scientists, architects, product owners, and business stakeholders to define technical strategy and scalable solutions
- Provide technical leadership and mentorship to data engineers and development teams, promoting best practices and engineering excellence
- Drive architectural decisions with data and solution architects to ensure scalability, security, reliability, and maintainability
- Design and oversee data warehouse and data lake solutions balancing business usability, performance, and sustainability
- Establish engineering standards for data modeling, ETL frameworks, pipeline reliability, monitoring, and operational excellence
- Lead end-to-end solution delivery aligned with business needs, architecture standards, and regulations
- Oversee production support and operational management of AWS-based data platforms, conducting root-cause analysis and performance tuning
- Champion data quality, governance, observability, and stewardship practices across teams and platforms
- Identify opportunities for data architecture modernization and operational efficiency through automation and cloud-native tech
Required Qualifications:
- 8+ years of experience in Data Engineering, including 5+ years in AWS ecosystems
- Expert-level experience with AWS services including S3, EMR, Glue Jobs, Lambda, Athena, CloudTrail, SNS, SQS, CloudWatch, and Step Functions
- Extensive experience designing and implementing enterprise-scale data lake and data warehouse solutions using Lake Formation, Amazon Redshift, and Amazon Athena
- Experience with Kafka-based streaming architectures, preferably Confluent Kafka
- Advanced SQL and data modeling expertise, including dimensional modeling, data vault, and large-scale data warehousing
- Deep experience developing and optimizing scalable, resilient data pipelines in AWS
- Strong understanding of distributed data processing frameworks, particularly PySpark and EMR
- Advanced Python skills with extensive hands-on PySpark experience
- Experience with Infrastructure as Code using Terraform
- Designing and implementing CI/CD frameworks with GitHub and GitHub Actions
- Knowledge of AWS IAM roles, policies, governance, and security best practices
- Experience with workflow orchestration tools such as AWS Step Functions, Apache Airflow, or similar
- Experience leading cloud migration, modernization, and enterprise data platform initiatives
- Understanding of data governance, metadata management, data quality, and observability principles
- Experience building AI-ready data pipelines and ML workflows, including feature engineering and MLOps
- Knowledge of LLMs, RAG, and vector databases for AI-powered applications
Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.