AWS Cloud Data Engineer

Based in San Antonio, Guidehouse Digital, LLC offers an on-site opportunity for an experienced AWS Cloud Data Engineer to join a collaborative data team. You will design, build, and maintain scalable data pipelines and processing solutions in AWS, partnering with DBAs, data scientists, and business stakeholders to migrate data, optimize performance, and uphold data quality and governance.

Benefits

• Medical, Rx, Dental & Vision Insurance
• Personal and Family Sick Time & Company Paid Holidays
• Parental Leave
• 401(k) Retirement Plan
• Group Term Life and Travel Assistance
• Voluntary Life and AD&D Insurance
• Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts
• Transit and Parking Commuter Benefits
• Short-Term & Long-Term Disability
• Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities
• Employee Referral Program
• Corporate Sponsored Events & Community Outreach
• Care.com annual membership
• Employee Assistance Program
• Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)
• Position may be eligible for a discretionary variable incentive bonus

Responsibilities

• Design, build, and maintain robust data pipelines and data processing solutions in the AWS cloud
• Collaborate with the AWS Cloud DBA to create end-to-end data solutions that migrate data from legacy applications to AWS, ensuring performance and reliability
• Apply hands-on AWS data services and modern data architecture patterns while working with DBAs, data scientists, and business stakeholders to deliver scalable data solutions
• Design and implement scalable data pipelines using AWS Glue, Step Functions, Lambda, and Kinesis; build ETL and ELT processes to ingest, transform, and load data into data warehouses and data lakes
• Architect and maintain data lakes using S3; implement data cataloging with AWS Glue Catalog; optimize data storage formats such as Parquet and Delta
• Design data warehouse solutions with Redshift and integrate with existing RDS/Aurora databases managed by the DBA team
• Develop real-time and batch data processing solutions using Kinesis Data Streams, Kinesis Analytics, EMR, and AWS Batch
• Create and maintain data models, schemas, and documentation; collaborate with the DBA team to optimize data access patterns and query performance across relational and analytical databases
• Build automated data quality checks, monitoring, and alerting systems; implement data governance policies and ensure compliance with data retention, privacy, and security requirements

Requirements

• US Citizenship or Green Card is required
• Ability to obtain and maintain a Federal or DoD public trust; adjudication must be approved prior to onboarding. An active public trust or suitability is preferred
• Bachelor’s degree in computer science, data engineering, or a related field; an additional four years of experience can be used in lieu of a degree
• Minimum six years of data engineering experience, with at least 3+ years in AWS cloud environments
• Strong expertise in AWS data services including S3, Glue, DMS, Athena, Redshift, EMR, Kinesis, and Lambda
• Proficiency in Python, Scala, or Java for data processing and pipeline development
• Experience with SQL and working knowledge of relational databases (PostgreSQL, Oracle) and NoSQL systems (DynamoDB, DocumentDB)
• Understanding of data modeling concepts for transactional and analytical workloads
• Experience with Infrastructure as Code tools (Terraform, CloudFormation, CDK) and CI/CD pipelines for data engineering workflows
• Strong analytical and problem-solving skills with attention to data quality and system reliability
• Proven ability to collaborate with database administrators, data scientists, and business stakeholders

Technologies

• AWS services: Glue, Step Functions, Lambda, Kinesis, S3, Glue Catalog, Redshift, RDS, Aurora, Kinesis Data Streams, Kinesis Analytics, EMR, AWS Batch
• Programming: Python, Scala, Java
• Databases: PostgreSQL, Oracle, DynamoDB, DocumentDB
• Infrastructure as Code / CI/CD: Terraform, CloudFormation, CDK
• DevOps / containers: Git, Docker, Kubernetes, ECS, EKS
• BI / Visualization: QuickSight, Tableau, PowerBI
• Data formats and processing: JSON, Avro, Parquet, ORC, Delta Lake
• Big data / orchestration: Apache Spark, Apache Airflow