Data Engineer

About the Role

We are seeking a highly skilled Data Engineer to join our team and play a pivotal role in driving enterprise-wide data initiatives. In this position, you will be responsible for designing, implementing, and optimizing robust data pipelines while ensuring the highest standards of data quality, consistency, and reliability. Your expertise will be instrumental in supporting modern data engineering solutions that empower our organization to make informed, data-driven decisions. This role requires a proactive approach to identifying and resolving data quality issues, collaborating closely with cross-functional teams, and maintaining comprehensive data documentation to uphold governance and compliance standards.

Key Responsibilities

• Data Pipeline Design and Optimization: Develop, enhance, and maintain efficient data pipelines that facilitate seamless data flow across systems, ensuring scalability and performance.
• Data Quality Assurance: Establish and enforce data quality standards by monitoring, validating, and cleansing data to eliminate inaccuracies and inconsistencies.
• ETL Process Support: Collaborate with stakeholders to design, implement, and optimize Extract, Transform, Load (ETL) processes that integrate data from multiple sources into unified, actionable datasets.
• Data Quality Rules and Controls: Develop and implement data quality rules, controls, and frameworks to proactively detect and mitigate issues before they impact business operations.
• Issue Resolution: Investigate and resolve data quality discrepancies, anomalies, and performance bottlenecks through systematic analysis and troubleshooting.
• Cross-Functional Collaboration: Work closely with Data Governance, Analytics, and IT teams to align data strategies with business objectives and ensure adherence to regulatory requirements.
• Documentation and Governance: Maintain accurate and up-to-date documentation of data sources, transformations, and lineage to support transparency, compliance, and knowledge sharing.

Qualifications

• Education: Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related quantitative field. Advanced degrees or relevant certifications are a plus.
• Experience: Minimum of five years of hands-on experience in data engineering, data quality management, or a closely related discipline, with a proven track record of delivering high-quality data solutions.
• Technical Proficiency: Strong expertise in SQL for complex querying and data manipulation, along with experience in ETL tools and frameworks such as Apache NiFi, Talend, Informatica, or similar platforms.
• Data Quality Methodologies: In-depth knowledge of data quality principles, including data profiling, cleansing, validation, and monitoring techniques to ensure data integrity.
• Cloud Platforms: Familiarity with cloud-based data platforms (e.g., AWS, Azure, or Google Cloud) and their associated services for data storage, processing, and analytics is highly advantageous.
• Analytical and Problem-Solving Skills: Exceptional analytical mindset with the ability to dissect complex data issues, identify root causes, and implement effective solutions in a timely manner.
• Communication and Collaboration: Strong interpersonal skills with the ability to articulate technical concepts to non-technical stakeholders and work collaboratively in a team-oriented environment.