Sr. Data Engineer

ProArch; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

ProArch seeks an experienced Data Engineer to architect scalable data pipelines and data architectures across data lake, warehouse, and mart environments. You will design semantic data models and dashboards to support enterprise reporting for internal and external stakeholders.

The role emphasizes governance, security, and performance optimization, with a focus on cloud-native services and scalable analytics frameworks across platforms.

Qualifications

• Bachelor's or master's degree in computer science, engineering, or related field.
• 8+ years of experience in data engineering with emphasis on governance and design.
• Experience building scalable data architectures for enterprise reporting.
• Strong knowledge of dimensional modeling (star/snowflake) and semantic modeling.
• Proficiency in Python, SQL, and PySpark for data solutions.
• Experience with cloud data platforms (AWS Redshift/S3/EMR/Lambda) and data governance tools.
• Familiarity with MLOps and AI data pipelines using cloud services.

Responsibilities

• Architect and implement scalable data pipelines for structured and unstructured data.
• Design end-to-end data solutions including Data Lake, Data Warehouse, and Data Mart.
• Develop Power BI semantic models, datasets, dashboards, and reports.
• Implement data governance including lineage, metadata management, and audits.
• Optimize data systems with partitioning, indexing, and security controls.

Skills

Data modeling

Power BI

Python

SQL

PySpark

Data governance

MLOps

Cloud data platforms

Education

Bachelor's or master's degree in CS/Engineering or related field

Tools

Erwin

SQL Data Modeler

AWS SageMaker

Glue Data Catalog

Redshift

S3

Databricks

Azure Synapse

Tableau

Job description

Key Responsibilities/ Accountabilities: Listing of key responsibilities / major activities necessary to fulfill the position’s purpose. If possible, please include the percentage of time spent on each key responsibility.

Advanced Data Engineering and Solution Design (80%)

• Architect and implement scalable data pipelines to process and integrate structured and unstructured data.
• Design end-to-end data solutions, including Data Lake, Data Warehouse, and Data Mart, to support analytics and operational systems.
• Leverage UDP framework to consolidate data pipelines across healthcare domains.
• Support the integration of new data domains through standardized ingestion and transformation frameworks.
• Collaborate with stakeholders to translate business requirements into scalable, high-performing data architectures.
• Integrate and optimize data access across distributed systems using data federation and virtualization tools
• Develop reusable data assets to support self-service analytics across programs and business domains.
• Design and maintain enterprise dimensional data models including fact tables, conformed dimensions, star schemas, snowflake schemas, and analytical data marts.
• Translate business and reporting requirements into scalable analytical data structures and semantic data models.
• Develop and maintain semantic layers, curated datasets, and business views to support enterprise reporting and analytics.
• Design, develop, and maintain Power BI semantic models, datasets, dashboards, and reports for internal and external stakeholders.
• Create and optimize DAX measures, calculated columns, KPIs, and business metrics to support operational and strategic reporting.
• Implement Power BI best practices including Row-Level Security (RLS), deployment pipelines, performance optimization, and governance standards.
• Partner with business users and subject matter experts to gather reporting requirements and deliver actionable analytics solutions.
• Ensure consistency of business definitions, metrics, and calculations across enterprise reporting and analytics platforms.

Data Governance and Compliance (10%)

• Develop and enforce data governance standards, ensuring consistency, accuracy, and compliance with regulatory frameworks (e.g, HIPAA).
• Implement data lineage, metadata management, and auditability practices using tools like AWS Glue Data Catalog.
• Establish and manage data stewardship frameworks to improve data quality and trust across the organization.

Performance Optimization and Security (10%)

• Optimize system performance by designing and implementing data partitioning, indexing, and compression strategies.
• Ensure data security through access controls, encryption, and secure design practices.

Core Competencies

• Experience with enterprise data modeling tools (e.g., Erwin, SQL Data Modeler) and strong expertise in dimensional modeling methodologies including Star Schema, Snowflake Schema, Fact and Dimension design, and semantic modeling.
• Bachelor's or master's degree in computer science, Engineering, or related field.
• 8+ years of experience in data engineering, with a strong emphasis on data governance and solution design.
• Expertise in developing scalable data architectures for enterprise reporting
• Familiarity with MLOps and AI data pipelines leveraging cloud-native services such as AWS SageMaker, Glue ML, or Databricks for feature engineering and model deployment.
• Advanced knowledge of data governance tools and frameworks, including AWS Glue Data Catalog, to support enterprise-wide lineage, metadata, and compliance practices.
• Strong understanding of cloud data platforms and services – particularly AWS (Redshift, S3, EMR, Lambda) and hybrid integrations with Azure Synapse or equivalent modern data warehouse technologies.
• Proficiency in programming and scripting languages (Python, SQL, PySpark) for building testing and optimizing scalable data solutions.
• Advanced experience developing Power BI semantic models, datasets, dashboards, reports, DAX measures, Power Query transformations, Row-Level Security, and performance optimization. Experience with Tableau is a plus.

Additional Qualifications:

• Excellent analytical and troubleshooting skills with attention to detail.
• Strong communication skills to effectively articulate technical concepts to non-technical stakeholders.
• Ability to prioritize tasks in a dynamic environment and manage multiple initiatives simultaneously.
• Certifications in cloud, database, and programming are a plus.