CASE STUDY | seapeak
Seapeak
Modernizing HR ETL Pipelines with Databricks Lakehouse
INDUSTRY
Transportation & Logistics
SOLUTION AREA
HR Analytics
ETL Migration
Azure Databricks
Spark Structured Streaming
CI/CD & DevOps
TECHNOLOGY
The Challenge
Seapeak, a Canadian marine transportation organization was in the process of modernizing its data capabilities, adopting cloud technologies such as Azure and Databricks to support its growing operational and analytics needs. With a lean IT and data engineering team, the organization needed to transition legacy SQL-based ETL processes into a scalable, production-grade Databricks environment.
However, the internal team lacked the bandwidth and expertise to drive a full ETL migration while sustaining day-to-day responsibilities. Existing pipelines suffered from data quality issues, inconsistent performance, and limited support for modern analytics requirements. Leadership wanted not only a successful migration, but a co-creation model that would build internal capability and long-term ownership of Databricks development.
The Data Elephant Difference
Data Elephant was selected for our local Vancouver presence, industry expertise, deep Databricks and Azure experience and collaborative project scoping and delivery approach. Over a focused six-week engagement, a dedicated Architect and Data Engineer worked side-by-side with the client’s team to modernize HR ETL pipelines and establish a scalable Lakehouse foundation.
Unified Data Foundations by implementing Unity Catalog for centralized security, lineage, and metadata within Azure Databricks
Connected Governance Framework that aligned Collibra’s governance capabilities with the technical controls in Databricks and Microsoft Fabric
Trusted Analytics through consistent data definitions and standardized KPIs in Power BI
Embedded Stewardship by establishing clear ownership and stewardship roles tied to business domains
Lean Delivery with a small, high-impact team focused on enabling results quickly
The Outcome
The organization successfully transitioned its HR ETL ecosystem to Databricks, unlocking improved data reliability, flexibility, and performance.
Results at a Glance
SUCCESSFUL MIGRATION
All HR ETL pipelines were rebuilt and deployed into Databricks, simplifying operations and reducing technical debt
VISIBILITY & TRUST
End-to-end data lineage through Unity Catalog and Collibra
IMPROVED QUALITY
Refined transformation logic and incremental processing delivered cleaner, faster data for analysts and HR stakeholders
ENHANCED PERFORMANCE
CDC-based pipelines and optimized Spark workloads accelerated processing and enabled support for both batch and streaming analytics
