IT engineer data lakehouse

Continental; India; On-site; INR 1,500,000 - 2,100,000; Full time

Benefits offered by this job

Training opportunities

Mobile and flexible working models

Sabbaticals

Job summary

Continental is seeking a data engineer to design, build, and operate scalable data pipelines in an Azure Databricks environment. You will ensure high data quality, implement lakehouse layers, and collaborate with SCM and IT stakeholders to deliver reliable analytics assets.

The role emphasizes modular code, TDD, CI/CD, and version control in a professional IDE. You'll work in a global, cross‑time‑zone team across India, Germany and the Philippines, using PySpark/Scala, and align with governance

Qualifications

• Degree in Computer Science, Data Engineering, Information Systems, or related discipline.
• Certifications in software development and data engineering (e.g., Databricks DE Associate, Azure Data Engineer, or relevant DevOps certifications).
• 3–6 years hands‑on experience in data engineering in enterprise environments.
• Proven experience building production‑grade codebases in IDEs with test coverage and version control.
• Experience in at least one business domain: SCM or similar.
• Experience mentoring junior developers or leading implementation workstreams is a plus.
• Experience working in international teams across multiple time zones and cultures, preferably with teams in India, Germany, and the Philippines.

Responsibilities

• Design scalable batch and streaming pipelines in Azure Databricks using PySpark or Scala.
• Implement ingestion from SAP, APIs, and flat files.
• Build bronze/silver/gold data layers following lakehouse architecture and governance.
• Develop data models (star/snowflake) for SCM needs.
• Ensure BI readiness via curated data marts and semantic models.
• Implement enterprise data warehouse models aligned with other domains.
• Develop and apply master data management strategies.
• Create automated data validation tests and CI/CD integration.
• Monitor pipelines and enforce data quality thresholds.
• Document data contracts, logic, and decisions in Markdown or auto‑docs.

Skills

Data pipelines

TDD

CI/CD

Version control

Agile

Cross-functional collaboration

Education

Databricks DE Associate certification

Azure Data Engineer certification

Bachelor's in Computer Science / Information Systems

Tools

PySpark

Scala

Job description

Job Description

Design, develop, and operate scalable and maintainable data pipelines in the Azure Databricks environment.

Develop all technical artefacts as code, implemented in professional IDEs, with full version control and CI/CD automation.

Enable data-driven decision-making in Supply Chain Management (SCM) by ensuring high data availability, quality, and reliability.

Implement data products and analytical assets using software engineering principles in close alignment with business domains and functional IT.

Apply rigorous software engineering practices such as modular design, test-driven development, and artifact reuse in all implementations.

Global delivery footprint; cross-functional data engineering support across SCM domains.

Collaboration with business stakeholders, functional IT partners, product owners, architects, ML/AI engineers, and Power BI developers.

Agile, product-team structure embedded in an enterprise-scale Azure environment.

Main Tasks

• Design scalable batch and streaming pipelines in Azure Databricks using PySpark and/or Scala.
• Implement ingestion from structured and semi-structured sources (e.g., SAP, APIs, flat files).
• Build bronze/silver/gold data layers following the defined lakehouse layering architecture & governance.
• Implement use-case driven dimensional models (star/snowflake schema) tailored to SCM needs.
• Ensure compatibility with reporting tools (e.g., Power BI) via curated data marts and semantic models.
• Implement enterprise-level data warehouse models (domain-driven 3NF models) for SCM data, closely aligned with data engineers for other business domains.
• Develop and apply master data management strategies (e.g., Slowly Changing Dimensions).
• Develop automated data validation tests using frameworks.
• Monitor pipeline health, identify anomalies, and implement quality thresholds.
• Establish data quality transparency by defining and implementing meaningful data quality rules with source system and business stakeholders and implementing related reports.
• Develop and structure pipelines using modular, reusable code in a professional IDE.
• Apply test-driven development (TDD) principles with automated unit, integration, and validation tests.
• Integrate tests into CI/CD pipelines to enable fail‑fast deployment strategies.
• Commit all artifacts to version control with peer review and CI/CD integration.
• Work closely with Product Owners to refine user stories and define acceptance criteria.
• Translate business requirements into data contracts and technical specifications.
• Participate in agile events such as sprint planning, reviews, and retrospectives.
• Document pipeline logic, data contracts, and technical decisions in markdown or auto-generated docs from code.
• Align designs with governance and metadata standards (e.g., Unity Catalog).
• Track lineage and audit trails through integrated tooling.
• Profile and tune data transformation performance.
• Reduce job execution times and optimize cluster resource usage.
• Refactor legacy pipelines or inefficient transformations to improve scalability.

Additional Information

The well-being of our employees is important to us. We offer exciting career prospects and support you in achieving a good work‑life balance with additional benefits such as:

• Training opportunities
• Mobile and flexible working models
• Sabbaticals

and much more...

Equal Opportunity

Diversity, Inclusion & Belonging are important to us and make our company strong and successful. We offer equal opportunities to everyone – regardless of age, gender, nationality, cultural background, disability, religion, ideology or sexual orientation.

Qualifications

Degree in Computer Science, Data Engineering, Information Systems, or related discipline.

Certifications in software development and data engineering (e.g., Databricks DE Associate, Azure Data Engineer, or relevant DevOps certifications).

3–6 years of hands‑on experience in data engineering roles in enterprise environments. Demonstrated experience building production‑grade codebases in IDEs, with test coverage and version control.

Proven experience in implementing complex data pipelines and contributing to full lifecycle data projects (development to deployment).

Experience in at least one business domain: SCM or a comparable field.

Experience mentoring junior developers or leading implementation workstreams is a plus.

Experience working in international teams across multiple time zones and cultures, preferably with teams in India, Germany, and the Philippines.

Company Description

Continental develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the technology company offers safe, efficient, intelligent, and affordable solutions for vehicles, machines, traffic and transportation. In 2023, Continental generated sales of €41.4 billion and currently employs around 200,000 people in 56 countries and markets.

Guided by the vision of being the customer’s first choice for material-driven solutions, the ContiTech group sector focuses on development competence and material expertise for products and systems made of rubber, plastics, metal, and fabrics. These can also be equipped with electronic components in order to optimize them functionally for individual services. ContiTech’s industrial growth areas are primarily in the areas of energy, agriculture, construction, and surfaces. In addition, ContiTech serves the automotive and transportation industries as well as rail transport.

The IT Digital and Data Services Competence Center of ContiTech caters to all the Business Areas in ContiTech and is responsible among other areas of Data & Analytics, Web and Mobile Software Development and AI.

The team for Data services specializes in all platforms, business applications and products in the domain of data and analytics, covering the entire spectrum including AI, machine learning, data science, data analysis, reporting and dashboarding.