Database Engineer - onsite

Eccalon, LLC
Detroit, MI, United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Data Analysis Big Data Cloud Computing Cloud Database Cloud Engineering Cluster Analysis Information Systems Databases Data Integration Extract Transform Load (ETL) Data Warehousing Database Development
+29 more
Dimensional Modeling Greenplum Meta-Data Management Metadata Repositories Microsoft SQL Server Online Analytical Processing Oracle (Applications) Performance Tuning Query Optimization Power BI Standard Sql SQL Stored Procedures Tableau (Software) Teradata SQL Freeform SQL System Availability Snowflake Database Performance Indexer Kubernetes Information Technology Data Lineage Google Bigquery Vertica Azure Synapse Analytics Looker Analytics Data Pipelines Sql Tuning Amazon Redshift

Job description

We are seeking a highly skilled Database Engineer with deep expertise in Data Warehousing to design, build, optimize, and maintain large-scale analytical databases that support reporting, business intelligence, and advanced analytics use cases. This role is responsible for ensuring data correctness, performance, scalability, and reliability across enterprise data warehouse platforms. The ideal candidate has strong experience with dimensional modeling, SQL performance tuning, data pipelines, and modern cloud or on-prem data warehousing technologies., * Data Warehouse Architecture & Design

  • Design, implement, and maintain enterprise-grade data warehouse architectures
  • Develop and manage dimensional data models (star, snowflake, fact and dimension tables)
  • Translate business and analytical requirements into scalable data schemas
  • Support historical, slowly changing dimensions (SCD), and aggregations

  • Database Development & Optimization
  • Write and optimize complex SQL queries, views, materialized views, and stored procedures
  • Tune database performance for large-scale analytical workloads
  • Implement partitioning, indexing, clustering, and distribution strategies
  • Ensure high availability, backup, recovery, and disaster-recovery readiness

  • Data Integration & Pipelines
  • Support and optimize ELT/ETL pipelines feeding the data warehouse
  • Collaborate with data engineers to ensure reliable ingestion from source systems
  • Validate data quality, consistency, and integrity across datasets
  • Partner with analytics and BI teams to ensure data readiness and usability

  • Platform Operations & Governance
  • Monitor and maintain warehouse performance, cost, and usage efficiency
  • Implement data access controls, security policies, and governance standards
  • Maintain documentation for schemas, metrics, and data definitions
  • Support audit, compliance, and data lineage requirements

  • Collaboration & Leadership
  • Work closely with analytics, product, finance, and business stakeholders
  • Provide guidance on best practices for querying and modeling
  • Contribute to architectural discussions and platform evolution
  • Mentor junior database or data engineers when applicable

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience)
  • 5+ years of experience as a Database Engineer, Data Engineer, or Data Warehouse Engineer
  • Expert-level SQL skills with experience handling large datasets
  • Strong experience designing and operating data warehouses for analytics and BI
  • Cloud Data Warehouses: Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse
  • On-Prem / MPP Databases: Teradata, Oracle, SQL Server, Vertica, Greenplum
  • OLAP / Analytics Concepts: Columnar storage, MPP architectures, query optimization
  • Strong knowledge of data modeling methodologies (Kimball, Inmon)
  • Experience with ELT/ETL tools and orchestration frameworks
  • Understanding of data partitioning, compression, and workload management
  • Familiarity with BI tools (Tableau, Power BI, Looker, etc.)
  • Experience with cloud infrastructure, cost optimization, and scaling strategies
  • Exposure to metadata management, data catalogs, and governance tools

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