Database Engineer - onsite

Eccalon, LLC; Detroit (MI); On-site; USD 120,000 - 160,000; Full time

Job summary

Eccalon, LLC in Detroit seeks a highly skilled Database Engineer to design, build, optimize, and maintain large-scale analytical databases for reporting, BI, and advanced analytics.

The role focuses on dimensional modeling, SQL performance tuning, ELT/ETL pipelines, data correctness, and governance across cloud and on-premises data warehouses. Collaboration with analytics, product, and finance teams is essential.

Qualifications

• Bachelor's degree or equivalent experience.
• 5+ years as Database/Data/Warehouse Engineer.
• Expert-level SQL for large datasets.
• Strong analytics and BI data modelling experience.
• Experience with Snowflake/Redshift/BigQuery/Azure Synapse.

Responsibilities

• Data Warehouse architecture, design and optimization.
• Develop and manage dimensional models (star/snowflake).
• Translate requirements to scalable schemas and pipelines.
• Tune performance of large analytical workloads.
• Manage ELT/ETL pipelines and data ingestion.
• Implement partitioning, indexing, and data governance.

Skills

SQL performance tuning

Data warehousing design

Dimensional modeling

Cloud data warehouses

Data governance

ETL/ELT tooling

BI tools familiarity

SQL strong programmer

Performance optimization

Education

Bachelor’s degree in Computer Science or related field

Tools

Snowflake

Amazon Redshift

Google BigQuery

Azure Synapse

Tableau / Looker / Power BI

ETL orchestration tools

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.

Responsibilities

• 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
• 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
• 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

Required Qualifications

• 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
• 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