• Responsible for the design, development, testing, and implementation of the new generation of data movement solutions for the Bank using state of the art technologies to optimize effectiveness of Provident Bank’s data warehouse. • Design, develop, test, and implement ETL/ELT data movement jobs based on business requirements to feed data into Provident’s data warehouse and the various downstream bank applications. • Provide technical guidance on data movement related issues and ensure optimal design for all aspects of the data warehouse. • Perform data analysis and sourcing to target mappings and verify accuracy of data within the Bank’s data warehouse. • Identify, design and implement process improvements (i.e. automate manual processes and optimize data delivery) to optimize the quality of data for the firm’s business intelligence team. • Implement, maintain, and extend best practices and assets in line with the market standards and guidelines to best ensure reliability of the Bank’s data.

Role Description We are seeking a talented Analytics Engineer / Data Engineer to join our dynamic Data & Analytics team. This role focuses on building scalable data solutions that support business decision-making through advanced data integration, transformation, and visualization processes. The successful candidate will work on developing and optimizing ETL pipelines, leveraging Databricks, Python, SQL, and collaborating with cross-functional teams to drive innovative analytics initiatives. - Develop and optimize ETL pipelines using Databricks to support data integration and processing. - Collaborate with stakeholders across technical and business teams to gather requirements and design scalable data solutions. - Manage the data lifecycle, from ingestion into the data lake (bronze, silver, gold tiers) to preparation for visualization. - Implement and maintain data processing logic using SQL and Python. - Support advanced analytics and machine learning operations within the Databricks environment. - Build and enhance dashboards and reports, with Sigma Computing as a preferred platform (Qlik is not required). - Apply Agile methodologies to enhance collaboration and efficiency across the analytics team. Qualifications - BS degree in Computer Science or a related subject. - 3 years of experience in a Data Engineer, Analytics Engineer, or similar role. - Advanced proficiency in SQL and Python for data transformation and automation. - Experience working with PySpark. - Experience working with Databricks or other data lake platforms. - Familiarity with the medallion architecture (bronze, silver, gold tiers). - Strong analytical mindset with experience in advanced analytics techniques. - Intermediate experience with ETL pipeline development and machine learning operations. - Familiarity with Agile methodologies and Sigma Computing (preferred but not required). - Excellent communication and collaboration skills. Requirements - Knowledge of AI and machine learning frameworks. - Experience with R is a plus. - Experience with data visualization tools (Qlik or similar tools). Soft Skills - Excellent problem-solving and analytical skills. - Collaborate seamlessly with technical and non-technical stakeholders to understand and address their analytical needs. - Utilize agile methodologies to identify complex issues and implement effective solutions in a timely manner. Benefits - Join a powerful tech workforce and help us change the world through technology. - Professional development opportunities with international customers. - Collaborative work environment. - Career path and mentorship programs that will lead to new levels. Company Description Global Technology Services is a rapidly expanding organization situated in Medellín, Colombia. We pride ourselves on possessing one of the most influential networks within software development and IT services for the entertainment, financial, and logistics sectors. Our corporate projections offer a multitude of opportunities for professionals to elevate their careers and experience substantial growth. Joining our team means engaging with expansive engineering teams across Latin America and the United States, contributing to cutting-edge developments in multiple industries.

Role Description As a Software Asset Data Supervisor, reporting to the Manager, SAM Enablement and PresSales, you will be responsible for SAM data program execution. You will lead a team responsible for the collection, validation, and management of software asset data, ensuring accuracy and compliance with enterprise standards. This is a hands-on leadership role, where you will supervise direct reports while also contributing to data collection, verification, and process optimization. You will collaborate with vendors, internal teams, and enterprise customers to streamline software asset reporting and maintain a high standard of data integrity. What you’ll do: - Supervise and mentor a team of Software Asset Data Coordinators, providing guidance and performance feedback. - Own and manage SAM data programs, ensuring successful delivery and continuous improvement. - Lead and drive expansion programs to grow customer engagement and service adoption. - Support vendor expansion and onboarding initiatives across the team. - Ensure timely and accurate collection, validation, and reporting of software asset data. - Assign workloads, track progress, and resolve roadblocks for the team. - Develop and maintain best practices for software asset data management. - Oversee and participate in the collection of Installation Base Reports (IBRs) from customers and vendors. - Act as the escalation point for vendor coordination and issue resolution. - Ensure all software asset data is approved, validated, and documented in compliance with company policies. - Verify software asset data for accuracy, consistency, and completeness. - Maintain and update the software asset management (SAM+) tool with verified data. - Identify and address data discrepancies in coordination with vendors and internal teams. - Identify opportunities for process automation, efficiency improvements, and data quality enhancements. - Develop and enforce standard operating procedures (SOPs) for data collection and validation. Qualifications - 5+ years of experience in software asset management, IT operations, or data coordination. - Post secondary preferred. - Strong data management, reporting, and analysis skills with experience in software asset tracking tools. - Experience working with enterprise software vendors and IT procurement teams. - Excellent problem-solving and process improvement skills. - Ability to lead and motivate a team in a fast-paced operational environment. - Strong communication skills for interacting with vendors, customers, and internal stakeholders. Compensation A reasonable estimate of the current base pay range for this position is $69,750 to $93,000 annually + 8% Target Incentives. Actual salary will be based on a variety of factors, including location, experience, skill set, education, and related certification. The range for this position in other geographic locations may differ. Benefits - Health and Wellbeing: Medical and Dental Care, Employee & Family Assistance Program. - Financial Benefits: RRSP/DPSP Retirement Savings Plan with Company Matching, Life and Disability Insurance. - Paid Time Off: Vacation and Sick Leave, Holidays, Parental Leave, Volunteer Days, Bereavement Leave. - Additional Perks: Employee Discount Program. Inclusion & Equal Opportunity Employment We are an equal opportunity employer committed to diversity, inclusion & belonging. People seeking employment at Softchoice are considered without regard to any protected category including but not limited to, race, color, religion, national origin, age, sex, marital status, ancestry, disability, veteran status, gender identity, or sexual orientation. Require Accommodation? We are proud to provide interview & employment accommodation during the recruitment and hiring process. If you require any accommodation to apply or interview for a position, please reach out directly to asktalentacquisition@softchoice.com . We are committed to working with you to best meet your needs. Our Commitment to Your Experience We are committed to the safety of all applicants and team members. With that in mind, we have implemented digital interviewing for everyone. We understand that you may need to interview with distractions around you (such as children or furry friends) and we will be doing the same. Before you start with us, we will conduct a criminal record check, verify your education, and check your references. When you join Softchoice, we will onboard you remotely. Don't worry. It's quick, simple and you'll be connected with your new team in no time. Job Requisition ID 7416

• Lead architecture and design of complex data pipelines on Databricks lakehouse architecture (Unity Catalog, Delta Lake, Structured Streaming) • Define technical approach for data engineering initiatives, mentor less-senior engineers, and set standards for code quality through leadership and code reviews • Design and build data foundations that enable AI/ML capabilities — feature stores, embedding pipelines, vector search indexes, and model training datasets • Align data engineering solutions with business strategy, including support for Agentic AI workloads • Own health, scalability, and modernization of data infrastructure with Databricks as the strategic platform — including workload migration, compute optimization, and Unity Catalog adoption • Optimize pipeline performance (Delta Lake table layouts, clustering, Z-ordering) and establish monitoring/alerting best practices with clear SLAs • Build data infrastructure supporting Agentic AI systems — real-time data access layers, context retrieval pipelines, and agent-accessible data services • Collaborate cross-functionally with DevOps, Platform Engineering, and MLOps roles to integrate data solutions into the broader technology environment and shared AI infrastructure – Mlflow registries, feature stores, and agent orchestration layers • Provide consultation to Senior Leadership on complex projects and drive continuous improvement initiatives • Champion data governance at all layers for data, models, and AI assets • Implement data quality strategies (master data management, validation rules, Delta Live Tables expectations) to ensure trust in enterprise data • Serve as liaison across data engineering, AI engineering, and business teams; promote data literacy and stewardship