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