• Architect and oversee the implementation of enterprise-grade data solutions, ensuring scalability, reliability, and performance.

• Define and enforce data engineering standards, best practices, and governance policies across the organization.

• Lead the design and optimization of complex data pipelines and workflows for diverse data sources.

• Ensure data quality, consistency, and security across all stages of the data lifecycle.

• Drive automation strategies to improve operational efficiency and reduce manual interventions.

• Collaborate with senior stakeholders to align data engineering solutions with business objectives and long-term strategies.

• Stay ahead of emerging technologies and trends to drive innovation in data engineering practices.

• Mentor and guide mid-level and junior engineers, fostering a culture of knowledge sharing, continuous improvement, and technical excellence.

• Lead cross-functional collaboration to ensure alignment between data engineering, product, and business teams.

• Provide strategic leadership to the data engineering team, ensuring alignment with organizational goals and priorities.

• Manage team performance through regular feedback, goal setting, and performance reviews.

• Identify skill gaps and provide training or development opportunities to enhance team capabilities.

• Act as a trusted advisor to senior stakeholders, providing insights and recommendations on data engineering strategies.

• Build and maintain a high-performing team by fostering a culture of accountability, innovation, and collaboration.

• Oversee resource planning, recruitment, and onboarding to ensure the team is adequately staffed and skilled.

• Bachelor’s degree or above in computer science, Information Systems, or a related field.

• 5+ years of work experience in data engineering or ETL development, with domain-level ownership experience.

• Advanced knowledge of cloud platforms (e.g., GCP BigQuery, Dataflow, AWS/Azure equivalents).

• Proficiency in programming languages such as Python, Java, or Scala for data processing and pipeline development.

• Familiarity with orchestration tools and workflow automation frameworks (e.g., Apache Airflow, Cloud Composer).

• Cloud certifications (e.g. GCP Professional Data Engineer, AWS Big Data Specialty) are a strong plus.

• Ability to analyze complex data sets, identify patterns, and derive actionable insights.

• Strong troubleshooting and optimization skills to ensure reliability and performance.

• Experience working with cross-functional teams to translate business requirements into scalable technical solutions.

• Proven ability to lead and mentor mid-level and junior engineers, fostering a culture of knowledge sharing and continuous improvement.

• Strong leadership and decision-making skills to manage team performance and deliver results.

• Ability to manage resource planning, recruitment, and onboarding to ensure the team is adequately staffed and skilled.

• Excellent communication skills to influence stakeholders and align team efforts with organizational goals.

• Strategic mindset to drive innovation and align data engineering solutions with long-term business objectives.