Job Opening for Data Engineer (Job Code RT 1485).

Job Title: Data Engineer
Job Location: Remote
Employment Type: Contract
Experience Required: 3+ years

Educational Qualification: Advanced degree in Computer Science, Engineering, Data Science, AI, or a related field

Synopsis:

We are seeking a highly motivated Data Engineer to join our expanding Data & AI team. This role offers the opportunity to design and develop robust, scalable data pipelines and infrastructure, ensuring the delivery of high-quality, timely, and accessible data throughout the organization. As a Data Engineer, you will collaborate across teams to build and optimize data solutions that support analytics, reporting, and business operations. The ideal candidate combines deep technical expertise, strong communication, and a drive for continuous improvement.

Who You Are:

• Experienced in designing and building data pipelines for ingestion, transformation, and loading (ETL/ELT) of data from diverse sources to data warehouses or lakes.

• Proficient in SQL and at least one programming language, such as Python, Java, or Scala.

• Skilled at working with both relational databases (e.g., PostgreSQL, MySQL) and big data platforms (e.g., Hadoop, Spark, Hive, EMR).

• Competent in cloud environments (AWS, GCP, Azure), data lake, and data warehouse solutions.

• Comfortable optimizing and managing the quality, reliability, and timeliness of data flows.

• Ability to translate business requirements into technical specifications and collaborate effectively with stakeholders, including data scientists, analysts, and engineers.

• Detail-oriented, with strong documentation skills and a commitment to data governance, security, and compliance.

• Proactive, agile, and adaptable to a fast-paced environment with evolving business needs.

What You Will Do:

• Design, build, and manage scalable ETL/ELT pipelines to ingest, transform, and deliver data efficiently from diverse sources to centralized repositories such as lakes or warehouses.

• Implement validation, monitoring, and cleansing procedures to ensure data consistency, integrity, and adherence to organizational standards.

• Develop and maintain efficient database architectures, optimize data storage, and streamline data integration flows for business intelligence and analytics.

• Work closely with data scientists, analysts, and business users to gather requirements and deliver tailored data solutions supporting business objectives.

• Document data models, dictionaries, pipeline architectures, and data flows to ensure transparency and knowledge sharing.

• Implement and enforce data security and privacy measures, ensuring compliance with regulatory requirements and best practices.

• Monitor, troubleshoot, and resolve issues in data pipelines and infrastructure to maintain high availability and performance.

Preferred Qualifications

• Bachelor’s or higher degree in Computer Science, Information Technology, Engineering, or a related field.

• 3-4years of experience in data engineering, ETL development, or related areas.

• Strong SQL and data modelling expertise with hands-on experience in data warehousing or business intelligence projects.

• Familiarity with AWS data integration tools (e.g., Glue, Athena), messaging/streaming platforms (e.g., Kafka, AWS MSK), and big data tools (Spark, Databricks).

• Proficiency with version control, testing, and deployment tools for maintaining code and ensuring best practices.

• Experience in managing data security, quality, and operational support in a production environment.

What You Deliver

• Comprehensive data delivery documentation (data dictionary, mapping documents, models).

• Optimized, reliable data pipelines and infrastructure supporting the organization’s analytics and reporting needs.

• Operations support and timely resolution of data-related issues aligned with service level agreements.

Interdependencies / Internal Engagement

• Actively engage with cross-functional teams to align on requirements, resolve issues, and drive improvements in data delivery, architecture, and business impact.

• Become a trusted partner in fostering a data-centric culture and ensuring the long-term scalability and integrity of our data ecosystem