Data Engineer Lead

DigiValet is looking for a detail-oriented and business-savvy Data Engineer Lead to join our growing data engineering team. In this role, you will be responsible for turning data into actionable insights that drive strategic decisions. You will collaborate with cross-functional teams to deliver impactful dashboards, conduct deep-dive analyses, and support data-driven decision-making.

Key Responsibilities:

1. KPI to Insight Conversion

• Collaborate with business stakeholders to understand key performance indicators (KPIs) and their impact on business objectives.
• Translate business questions and KPIs into analytical frameworks and data requirements.
• Apply advanced analytical techniques to uncover underlying drivers and correlations within KPI data.
• Develop insightful visualisations and reports that effectively communicate KPI trends and patterns.
• Provide actionable recommendations to improve KPI performance and achieve business goals.

2. Data Engineering and Processing (Databricks/PySpark)

• Design, develop, and maintain scalable data pipelines using Databricks and PySpark.
• Perform ETL (extraction, transformation, loading) from diverse data sources.
• Ensure data quality, consistency, and integrity through rigorous data cleaning and validation.
• Optimize data storage and retrieval for efficient analysis and reporting.

3. Statistical Analysis and Modeling

• Conduct exploratory data analysis (EDA) to identify patterns, trends, and anomalies.
• Apply statistical techniques (e.g., hypothesis testing, regression analysis) to validate findings and quantify relationships.
• Develop and implement predictive and prescriptive models using machine learning algorithms.
• Evaluate model performance and iterate to improve accuracy and robustness.

4. AI/ML Development and Deployment

• Build and deploy machine learning models using frameworks like scikit-learn, TensorFlow, or PyTorch.
• Implement AI solutions to address specific business challenges and optimize KPI performance.
• Monitor and maintain deployed models, ensuring optimal performance and scalability.
• Apply MLOps best practices for continuous integration and deployment.

5. Insights and Communication

• Translate complex data insights into clear, concise, and actionable recommendations.
• Create compelling visualisations and dashboards to communicate findings effectively.
• Present data-driven insights to both technical and non-technical audiences.
• Document all code, models, and analytical processes for transparency and reproducibility.

Required Skills :

• 5+ years of hands-on experience in data analytics or business intelligence roles.
• Proficient in SQL (writing complex queries, joins, subqueries, CTEs, window functions).
• Strong expertise in data modeling, and report/dashboard creation.
• Experience working with Databricks or other modern data platforms (e.g., Snowflake, BigQuery, Redshift).
• Working knowledge of Python for data manipulation and visualisation.
• Understanding of data warehousing concepts, lakehouse architectures, and data integration.
• Excellent problem-solving, communication, and stakeholder management skills.

Personality Attributes:

• Self-starter and confident.
• Team player with positive attitude and open mindedness for learning.

What we offer?

• Interesting and challenging work in mid-size and fast-growing company.
• Exciting projects involving cutting edge technologies (Artificial Intelligence, IoT, Voice Technology, Virtual Reality).
• Professional development opportunities.
• Modern and comfortable office facilities.
• Excellent benefits and compensation package.
• The company is all about new technologies. Don't restrict yourself to the ongoing developments other than that you can come up with your new ideas and will be appreciated.

Imagine yourself working as Data Engineer Lead here at DigiValet. The company promotes a friendly working environment breaking the cliche office hierarchy system.