AWS Redshift Data Engineer
- SBase Technologies Inc.
18 Days Ago
NA
W2
Remote
6-10 Years
Required Skills: AWS, Cloud, Data Engineering, SQL, Python, Spark, Failover, Monitoring, Troubleshooting.
Job Description
We are seeking an experienced AWS Redshift Data Engineer to design, develop, optimize, and support enterprise data solutions supporting business intelligence and analytics. The ideal candidate will have strong Amazon Redshift, AWS data engineering, performance optimization, business analysis, customer engagement, production support, and team mentoring experience.
Key Responsibilities
Design, develop, and optimize enterprise data warehouse solutions using Amazon Redshift and AWS services.
Partner with business users and technical teams to gather requirements, perform data analysis, and define source-to-target mappings.
Translate business requirements into scalable data models and ETL/ELT solutions.
Develop and optimize SQL queries, Redshift schemas, and data loading processes.
Perform Redshift performance triage, including query bottleneck analysis, workload contention, resource utilization, and production troubleshooting.
Configure and manage Redshift Workload Management (WLM), workload queues, prioritization, and workload optimization.
Implement Redshift query auditing, monitoring, query logs, system tables, and audit requirements.
Ensure data quality through validation, profiling, root cause analysis (RCA), and governance best practices.
Perform Disaster Recovery (DR) planning, implementation, testing, and failover activities for AWS/Redshift environments.
Implement and support AWS IAM / IDC security administration, access controls, and secure enterprise connectivity.
Identify and implement AWS/Redshift cost optimization opportunities, including workload optimization, resource right-sizing, and cost containment.
Support Amazon SageMaker environments, including administration, permissions, endpoints, monitoring, troubleshooting, and production support.
Lead customer workshops to define business objectives, reporting requirements, and data solutions.
Collaborate with architects, developers, analysts, and project managers to deliver scalable, high-quality solutions.
Maintain technical documentation, including mapping specifications, data dictionaries, and process flows.
Recommend improvements to data architecture, automation, performance, security, and cloud best practices.
Provide technical support for production data environments, including incident troubleshooting and resolution.
Leadership & Mentoring
Mentor, coach, and train a highly skilled team of data engineers.
Conduct design and code reviews while promoting engineering best practices.
Provide technical leadership throughout project delivery and production support.
Establish development standards, coding practices, and data engineering methodologies.
Guide team members on troubleshooting, performance optimization, and production support best practices.
Required Qualifications
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
7+ years of data engineering or data warehousing experience.
5+ years of hands-on Amazon Redshift experience.
Advanced SQL and dimensional data modeling expertise.
Strong hands-on experience with Redshift Performance Triage and optimization.
Hands-on experience with Redshift Workload Management (WLM).
Experience with Redshift query auditing, monitoring, and troubleshooting.
Experience with AWS IAM / IDC security administration and access management.
Experience with Disaster Recovery planning and testing in AWS/Redshift environments.
Experience with AWS/Redshift cost optimization and cost containment.
Hands-on experience with Amazon SageMaker administration and production support.
Experience with AWS services such as Glue, S3, Lambda, Step Functions, and/or EMR.
Strong knowledge of data mapping, profiling, metadata management, and data quality.
Strong production support and troubleshooting experience.
Excellent communication and customer-facing consulting skills.
Proven experience mentoring and developing technical teams.
Preferred Qualifications
AWS Certified Data Engineer or AWS Certified Solutions Architect.
Experience with Python, Spark, and Agile methodologies.
Knowledge of Power BI, Tableau, or Amazon QuickSight.
Experience with enterprise data governance, security, audit, and compliance.
Experience supporting large-scale, high-volume AWS Redshift production environments.
Experience with cloud data warehouse architecture and performance optimization.
Technical Skills:-
AWS / Cloud: AWS Redshift, S3, Glue, Lambda, Step Functions, EMR, SageMaker, IAM, IDC, CloudWatch
Data Engineering: ETL/ELT, Data Warehousing, Dimensional Modeling, Data Mapping, Data Profiling, Metadata Management, Data Quality
Redshift: Performance Triage, Query Optimization, WLM, Workload Management, Query Auditing, Monitoring, Schema Design, Data Loading, Cost Optimization
Database / Programming: Advanced SQL, Python, Spark
Operations: Production Support, RCA, Disaster Recovery, DR Testing, Failover, Monitoring, Troubleshooting
Leadership: Technical Leadership, Mentoring, Coaching, Code Reviews, Design Reviews, Customer Workshops
Success Factors
The ideal consultant combines strong AWS Redshift expertise with exceptional analytical and troubleshooting skills, customer engagement, production support experience, and the ability to mentor and develop a talented data engineering team while delivering scalable, secure, cost-efficient, and high-quality cloud data solutions.
