Data Engineer - AWS, Databricks & Delta Lake

Acuity INC; United States; Presencial; USD 120 000 - 140 000; Tempo integral

Resumo da oferta

Acuity Inc. seeks a Data Engineer to design and deliver AWS cloud-scale data platforms for federal clients. The role emphasizes Spark, Delta Lake, and distributed pipelines on Databricks, combining engineering with strategic enterprise data modernization.

Build PySpark pipelines, design Delta Lake tables, and develop ETL/ELT workflows while collaborating with data architects to ensure secure, scalable AWS storage and access. CI/CD with GitLab/Jenkins is expected.

Qualificações

• 4+ years of experience in data engineering and Agile analytics.
• 4+ years of experience creating software for retrieving, parsing and processing structured and unstructured data.
• 2+ years of experience building scalable ETL and ELT workflows for reporting and analytics.
• 2+ years experience building enterprise data engineering solutions in the cloud, with AWS and Databricks.
• Experience with data quality, validation frameworks, and storage optimization strategies.
• BA or BS degree

Responsabilidades

• Build and maintain scalable PySpark-based data pipelines in Databricks notebooks to support ingestion, transformation, and enrichment of structured and semi-structured data.
• Design and implement Delta Lake tables optimized for ACID compliance, partition pruning, schema enforcement, and query performance across large datasets.
• Develop ETL and ELT workflows that integrate multiple source systems into a centralized, query-optimized data warehouse architecture.
• Leverage Spark SQL and DataFrame APIs to implement business rules, dimensional joins, and aggregation logic aligned to warehouse modeling best practices.
• Collaborate with data architects and engineers to implement cloud-native data solutions on AWS using S3, Glue, RDS, and IAM for secure, scalable storage and access control.
• Optimize pipeline performance through intelligent partitioning, caching, broadcast joins, and adaptive query tuning.
• Deploy and version data engineering assets using Git-integrated development workflows and automate deployment with CI/CD tools such as GitLab or Jenkins.
• Monitor pipeline health, job execution, and cluster utilization using native Databricks tools and AWS CloudWatch, identifying bottlenecks and optimizing cost-performance tradeoffs.
• Conduct technical discovery and mapping of legacy source systems, identifying required transformations and designing end-to-end data flows.
• Implement governance practices including metadata tagging, data quality validation, audit logging, and lineage tracking using platform-native features and custom logic.
• Support ad hoc data access requests, develop reusable data assets, and maintain shared notebooks that meet operational reporting and analytics needs across teams.

Conhecimentos

Data engineering

Distributed pipelines

Spark

Delta Lake

Databricks notebooks

Query optimization

Data governance

Metadata tagging

Formação académica

Bachelor's degree

Ferramentas

Spark

Databricks

AWS

S3

Glue

RDS

IAM

GitLab

Jenkins

Descrição da oferta de emprego

Acuity Inc. seeks a Data Engineer to design and deliver AWS cloud-scale data platforms for federal clients. The role emphasizes Spark, Delta Lake, and distributed pipelines on Databricks, combining engineering with strategic enterprise data modernization.

Build PySpark pipelines, design Delta Lake tables, and develop ETL/ELT workflows while collaborating with data architects to ensure secure, scalable AWS storage and access. CI/CD with GitLab/Jenkins is expected.