IT Engineer, Data Lakehouse

Job not on LinkedIn

🕒 July 18

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 22%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Continental

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1871

💼 Consulting

📦 Logistics

🏭 Manufacturing

Consulting • Logistics • Manufacturing

Continental is a technology company that develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the company is focused on innovation in areas like autonomous mobility, connectivity, electric mobility, and safety technologies. Continental is a leader in developing smart and sustainable tire technologies and offers a wide range of industrial solutions. The company is committed to sustainability, emphasizing carbon neutrality, emission-free mobility, and a circular economy. With a global presence, Continental also offers extensive career opportunities across various fields, including software engineering, IT, and sales, contributing to the future of mobility solutions.

📋 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 • 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

🎯 Requirements

• 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. • Not required; however, 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.

🏖️ Benefits

• Training opportunities • Mobile and flexible working models • Sabbaticals and much more