Scotiatech is a world-class engineering group! We are seeking to modernize bank technology by delivering a trustworthy, unique, and top-quality service.

We want you to be part of a Team that is always in personal and professional growth, for this reason we are looking for our new DataOps Engineer Specialist.

What will you do?

- Data Integration: Integrate data across sources—including legacy on-premises into Azure Databricks—and validate end-to-end data flow so data lands complete and usable.
- Pattern Deployment & Architecture: Deploy and reuse the team’s approved ingestion, transformation, and integration patterns, partnering with architecture and senior engineers to follow the target design and standards.
- DataOps & Automation: Support DataOps practices (Git, CI/CD, automated testing, monitoring) to keep pipelines reliable, available, and performant.
- Discovery & Mapping: Explore legacy and GCP data, produce source-to-target mappings to the Delta Lake model, and document lineage and dependencies to support migration.
- Data Quality & Reconciliation: Check data quality and reconcile source vs. target (parity), cleansing and preparing data across the medallion layers (Bronze→Silver→Gold).
- SME Collaboration & Articulation: Work with SMEs to understand and clearly articulate what data means, and support cataloguing in Unity Catalog so data is discoverable and trusted.
- Reporting & Visibility: Build simple reports/dashboards (e.g., Power BI) on data availability and migration progress—by country, source, and owner.

What do we offer you?

ducation

- Bachelor’s degree in Computer Science, Data Engineering, Information Technology, Software Engineering, or a related field.
- A Master’s degree is considered a plus.
- Relevant cloud or data engineering certifications (Databricks, GCP, Azure, AWS) are considered a plus.

Experience





- Have a B1+ level of English.
- 3+ years of experience in DataOps, data integration, or data engineering support.
- Experience integrating and mapping data, and supporting data migration or cloud modernization (on-prem or GCP to Azure Databricks is an asset).
- Familiarity with DataOps practices (Git, CI/CD, automated testing, monitoring).
- Experience working with SMEs and cross-functional teams in an Agile environment.
- Strong proficiency in Apache Spark (PySpark) and Python for large-scale data processing.
- Knowledge of data migration, cloud modernization, and platform transformation initiatives is highly desirable.
- Strong SQL skills and experience working with large-scale analytical databases and data warehouses.
- Experience with data modeling, schema design, and data warehousing concepts.
- Understanding data governance, security, monitoring, and observability practices within cloud environments.
- Experience working in Agile delivery environments and collaborating with cross-functional teams.
- Understanding of data integration, ETL/ELT, and lakehouse/medallion patterns; Azure Databricks, Delta Lake, and Unity Catalog exposure is an asset.

Preferred Qualifications

- Databricks certifications (Data Engineer Associate/Professional) are highly desirable; Azure DP-203 is an asset.
- Experience with Lakehouse architecture and Delta Lake implementation.
- Familiarity with infrastructure-as-code tools such as Terraform.
- Exposure to data quality, data observability, and monitoring frameworks.
- Experience supporting cloud migration initiatives from on-premises or legacy platforms.

If you are seeking a fulfilling opportunity to join our esteemed team and contribute to the overall success, we invite you to apply for the role of DataOps Engineer Specialist. Take the next step in your career journey and make a significant impact today!

📌 DataOps Engineer Specialist (Colombia)
🏢 ScotiaTech
📍 Colombia