Data Analyst

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.

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