Role Overview
We are seeking a highly experienced
Engineering Manager to lead our
Power BI and Data Engineering team. This role requires a strategic thinker with deep technical expertise in
data analytics, data engineering, and business intelligence solutions, combined with strong leadership skills to manage and mentor a high-performing team.
You will be responsible for designing and implementing scalable data solutions, driving BI strategy, and ensuring seamless integration of data platforms to enable actionable insights across the organization.
Key Responsibilities
- Leadership & Strategy
- Lead and mentor a team of data engineers and BI developers.
- Define and execute the data engineering and BI roadmap aligned with business objectives.
- Collaborate with stakeholders to understand data requirements and deliver impactful solutions.
- Data Engineering & BI Development
- Must have experience as an Architect in implement robust data pipelines and ETL processes using modern tools and frameworks.
- Must have experience in Designing and optimizing data models for analytics and reporting.
- Must have experience in leading teams to Develop and maintain Power BI dashboards and reports for business-critical insights.
- Governance & Quality
- Establish best practices for data governance, security, and compliance.
- Ensure high data quality, reliability, and performance across all solutions.
- Innovation & Continuous Improvement
- Stay updated with emerging technologies in data engineering and BI.
- Drive automation and efficiency improvements in data workflows.
Required Qualifications
- Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
- Experience:
- 12+ years of experience in data engineering, BI development, and analytics.
- 5+ years in a leadership or managerial role overseeing technical teams.
- Technical Skills:
- Expertise in Power BI (DAX, Power Query, data modeling, dashboard design).
- Strong experience with data engineering tools (Azure Data Factory, Databricks, Synapse, SQL Server, etc.).
- Proficiency in SQL, Python, and ETL frameworks.
- Knowledge of cloud platforms (Azure preferred).
- Soft Skills:
- Excellent communication and stakeholder management skills.
- Strong problem-solving and decision-making abilities.
Preferred Qualifications
- Experience with Microsoft Fabric, Data Lake, and Azure Machine Learning, AI-driven analytics.
- Familiarity with Agile methodologies and DevOps practices for data solutions.
Key
KPIs for an Engineering Manager in this Role
- Data Engineering & BI Delivery
- On-Time Project Delivery:
- Percentage of data engineering and BI projects delivered on or before agreed timelines (Target: ≥95%).
- Dashboard/Report Accuracy:
- Accuracy of Power BI dashboards and reports compared to source data (Target: ≥99%).
- ETL Pipeline Reliability:
- Uptime and success rate of data pipelines (Target: ≥99.5%).
- Data Quality & Governance
- Data Quality Score:
- Reduction in data errors and inconsistencies across systems (Target: ≤1% error rate).
- Compliance Adherence:
- Percentage of data solutions meeting security and compliance standards (Target: 100%).
- Team Leadership & Development
- Employee Engagement & Retention:
- Team satisfaction score and retention rate (Target: ≥90%).
- Skill Development:
- Number of team members certified or trained in advanced BI/data engineering tools annually (Target: ≥80%).
- Business Impact
- Adoption Rate of BI Solutions:
- Percentage of business units actively using Power BI dashboards (Target: ≥90%).
- Decision-Making Efficiency:
- Reduction in time taken for business decisions due to improved data insights (Target: ≥20% improvement).
- Innovation & Continuous Improvement
- Automation Initiatives:
- Number of manual processes automated annually (Target: ≥10).
- Cost Optimization:
- Reduction in data infrastructure costs through optimization (Target: ≥15%).
