Data Engineer & Analyst – Data Pipelines & Analytics (Backend)

Job description

Join the Future of DHL DHL Group the logistics provider of the world with over 580,000 employees in more than 220 countries and territories. We are an organization that is not just moving goods around, we have a very clear purpose, and we are: Connecting People. Improving Lives. We provide challenges and opportunities for personal and professional development, we recognize the difference you bring to our business and together we share the pride of building one of the largest world leaders in logistics and supply chain.

Are you ready to shape the next generation of steering within one of the most dynamic logistics environments in the world? Our BI specialists for a German speaking country are at the forefront of transforming how data drives business decisions. We deliver real-time, business-critical insights across reporting, forecasting, and planning – empowering leadership with the intelligence needed to act with precision and speed.

But we don’t stop there. We are pioneering the digitalization of processes, integrating cutting-edge technologies and emerging trends to redefine how data creates value.

Our mission is clear

to turn information into impact and unlock measurable business advantage through smart, scalable, and future-proof solutions. What sets us apart is our strong team spirit – a culture of collaboration, mutual support, and shared ambition. We believe that the best ideas emerge when diverse minds come together, and we foster an environment where everyone contributes to shaping the future. If you're a visionary professional with a passion for data-driven strategy, digital innovation, and operational excellence – this is your opportunity to make a difference at scale.

Step into a role where your expertise fuels transformation. Shape the future with us.

Key Responsibilities

Data Pipeline Engineering Architect, develop, and maintain scalable and resilient data pipelines using Kubeflow and Python, enabling efficient ingestion, transformation, and enrichment Ensure seamless integration of various internal and external data sources into Snowflake, converting them into relational formats optimized for reporting and analytics. Build up operational frameworks for logging and monitoring across data pipelines and systems Data Modeling & AI/ML Enablement Design Snowflake-based data models tailored for AI/ML readiness, supporting e.g. predictive analytics, anomaly detection, or automated alerting systems.

• Collaborate with data scientists and business analysts to implement and maintain a robust machine learning life cycle
• Perform deep-dive data analyses to identify relevant business insights

Collaboration & Documentation

• Maintain comprehensive documentation and version control of data workflows, models, and pipelines using GitHub, ensuring transparency, reproducibility, and team-wide collaboration.

Actively contribute to data governance initiatives, promoting best practices in data quality, lineage, and compliance.

Education & Experience

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, or a related technical discipline. Minimum 3 years of hands-on experience in data engineering or analytics

Technical Skills

Strong proficiency in Kubeflow, Python, Snowflake, and SQL for data pipeline development and modeling (minimum 3 years experience) Solid understanding of AI/ML readiness, including data structuring, feature engineering, and model preparation. Advanced skills in Power BI for data visualization and GitHub for version control and workflow documentation. Soft Skills Excellent analytical thinking and problem-solving capabilities.

Strong communication skills in English (written and verbal) Ability to work independently and collaboratively in cross-functional teams, with a proactive and solution-oriented mindset.

Working Conditions Schedule

[Standard business hours/Flexible hours/Shift work] standard Indian business hours Remote Work: [Remote/Hybrid/ On-site ] options available: On-site only Global Coverage: May require occasional work outside standard hours Performance Metrics: Success measured by response time, resolution rate, and customer satisfaction scores Benefits Annual Leave: 42 days off apart from Public / National Holidays.

Medical Insurance

Self + Spouse + 2 children. An option to opt for Voluntary Parental Insurance (Parents / Parent -in-laws) at a nominal premium covering pre existing disease.