Lead Data Engineer

Role: Lead AWS Data Engineer

Function: Data Engineering

Location: Remote

Industry: Information Technology & Services, Management Consulting

About Company A digital engineering firm founded in 2020, headquartered in Tampa, Florida. The company delivers AI-driven digital transformation for enterprises across 25+ countries. It operates seven global delivery centers and employs 450+ professionals. Services span platform engineering, data analytics, quality engineering, digital customer experience, and supply chain modernization. In 2023, the company expanded its product engineering capabilities through an acquisition. It is fast-growing, ownership-driven, and focused on speed, agility, and client outcomes.

Position Overview This role owns the design, development, and production support of enterprise-grade data platforms and pipelines on AWS. The engineer will lead complex data initiatives end-to-end — from architecture decisions through deployment — while setting engineering standards and mentoring team members. The work directly enables analytics, reporting, and operational data capabilities for large enterprise clients across multiple industries.

Role & Responsibilities

• Design and build scalable, secure data architectures on AWS supporting enterprise analytics, reporting, and operational data needs using Redshift, Glue, S3, Lambda, DMS, MWAA, Kinesis, DynamoDB, and RDS.
• Develop and maintain robust ETL/ELT pipelines and orchestration frameworks using Python, PySpark, and SQL — covering batch and near real-time ingestion, transformation, and delivery.
• Design and implement dimensional data models, data marts, and enterprise data warehouse solutions including partitioning, normalization, and performance optimization strategies.
• Build data quality, validation, reconciliation, monitoring, and alerting frameworks to ensure end-to-end data integrity across the platform.
• Perform root cause analysis and resolve production incidents; own operational excellence across the data platform.
• Support CI/CD pipelines and infrastructure automation for data engineering workloads using Git-based version control and Terraform.
• Mentor engineers, lead code reviews, define deployment and documentation standards, and drive continuous improvement across the data engineering practice.

Must Have Criteria

• 8+ years in Data Engineering with significant hands-on experience building AWS-based data platforms at enterprise scale.
• Production-grade expertise with AWS data services: Redshift, Glue, S3, Lambda, DMS, MWAA (Apache Airflow), Kinesis, DynamoDB, and RDS.
• Advanced proficiency in Python, PySpark, and SQL for ETL/ELT development, transformation logic, and performance tuning.
• Proven experience designing dimensional data models, data warehouses, and data marts with partitioning and query optimization.
• Hands-on experience with Apache Airflow or MWAA for workflow orchestration in production environments.
• Experience with CI/CD practices, Git-based version control, and Infrastructure as Code using Terraform.
• Demonstrated ability to own production support — incident management, root cause analysis, and SLA adherence for data pipelines.

Nice to Have

• AWS Certification — Solutions Architect Associate or Professional.
• Experience with event-driven and streaming architectures at scale.
• Domain experience in eCommerce, Retail, or Digital Commerce data — customer, product, order, inventory, or marketing datasets.
• Exposure to data governance, lineage, and compliance frameworks (e.g., column-level security, PII handling).
• Experience delivering in Agile/Scrum environments with cross-functional product and business teams.

What We Offer

• Ownership of complex, greenfield and brownfield data platform initiatives for large enterprise clients across 25+ countries.
• Career growth in a firm that has doubled in scale since 2020 and continues to expand through acquisitions and new verticals.