Data Engineer
StoneGate-Technologies LLC
United States
1 day ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Amazon Web Services
Amazon S3
Business Analytics Applications
Data Analysis
Audit Trail
Computer Programming
Databases
Data Architecture
Information Engineering
Data Governance
Data Infrastructure
+39 more
Data Mart
Data Security
Data Systems
Data Warehousing
Dimensional Modeling
Distributed Systems
Python (Programming Language)
Metadata
Meta-Data Management
Performance Tuning
Power BI
Software Tools
Cloud Services
SQL Databases
Tableau (Software)
Unstructured Data
Virtualization Technology
Enterprise Data Management
Scripting
Feature Engineering
Delivery Pipeline
Indexer
Powerquery
Data Layers
Data Lakes
Pyspark
Information Technology
Data Lineage
Collibra
AWS Glue
Data Analytics
Star Schema
Operational Systems
Data Management
Machine Learning Operations
Azure Synapse Analytics
Data Pipelines
Serverless Computing
Databricks
Job description
- Responsible for designing and implementing advanced data solutions supporting Unified Data Platform (UDP), enabling integrated analytics, and reporting.
- This role strengthens the Data Analytics and Reporting Team’s mission to deliver unified, governed, and high-quality data for enterprise insights and operational efficiency.
- The Data Engineer will work closely with Data Architects and Subject Matter Experts to develop, deliver, and deploy advanced data, engineering analytics, and reporting solutions that have a high impact for our internal and external clients., 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.
Requirements
- Bachelor’s or Master’s Degree in Computer Science, Engineering, or related field.
- 4+ 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
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.
- 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.
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