AWS Cloud Data Engineer

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

Overview

Based in San Antonio, this onsite role centers on designing, building, and maintaining data pipelines and processing solutions within the AWS ecosystem. The position involves partnering with database administrators, data scientists, and business stakeholders to deliver scalable data capabilities that drive informed decisions.

Responsibilities

• Design and sustain end-to-end data pipelines and processing solutions in the AWS cloud.
• Collaborate with the AWS Cloud DBA to migrate data from legacy applications to the AWS platform, ensuring performance and reliability.
• Apply hands-on experience with AWS data services and modern data architecture patterns to deliver scalable solutions with cross-functional teams.
• Architect and implement scalable pipelines using AWS services such as AWS Glue, Step Functions, Lambda, and Kinesis.
• Build ETL and ELT processes to ingest, transform, and load data into data warehouses and data lakes from diverse sources.
• Design and maintain data lakes on S3, implement data cataloging with AWS Glue Catalog, and optimize storage formats like Parquet and Delta.
• Develop data warehouse solutions with Redshift and integrate them with existing RDS/Aurora databases managed by the DBA team.
• Develop real-time and batch processing solutions using Kinesis Data Streams, Kinesis Analytics, EMR, and AWS Batch.
• Create and maintain data models, schemas, and documentation.
• Work with the DBA team to optimize data access and query performance across relational and analytical databases.
• Establish 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.
• Must be able to OBTAIN and MAINTAIN a Federal or DoD Public Trust; candidates must obtain approved adjudication prior to onboarding with Guidehouse. ACTIVE PUBLIC TRUST or SUITABILITY is preferred.
• Bachelor’s degree in computer science, Data Engineering, or a related field; four years of additional experience may substitute for the degree.
• Minimum six years of data engineering experience, with at least three years in AWS cloud environments.
• Strong expertise with 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 for both 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 abilities with a focus on data quality and system reliability.
• Proven ability to collaborate effectively with DBAs, data scientists, and business stakeholders.

Technologies

• S3, Glue, DMS, Athena, Redshift, EMR, Kinesis, Lambda
• Python, Scala, Java
• SQL, PostgreSQL, Oracle, DynamoDB, DocumentDB
• Terraform, CloudFormation, CDK
• Kinesis Data Streams, Kinesis Analytics, AWS Batch
• Parquet, Delta, AWS Glue Catalog, RDS, Aurora
• Git, Docker, Kubernetes, ECS, EKS
• QuickSight, Tableau, PowerBI
• JSON, Avro, ORC
• Apache Spark, Apache Airflow

Travel

Up to 10 percent travel may be required.

Clearance

Ability to Obtain Public Trust.