Company: Continental

Website: Visit Website

Business Type: Enterprise

Company Type: Product

Business Model: B2B

Funding Stage: Series C

Industry: Retail

Salary Range: ₹ 15-30 Lacs PA

Key Skills

- Design, implement, and maintain secure and scalable data ingestion pipelines from a wide variety of source systems, including SAP, SalesForce, SharePoint, APIs, and (legacy) manufacturing platforms.
- Build and enhance metadata-driven services that enable discoverability, access governance, and operational transparency of enterprise data.
- Serve as a technical expert and cross-functional enabler for structured and unstructured data acquisition, quality, and compliance.
- Establish and maintain holistic data quality management, monitoring and reporting.
- Contributes to a global data engineering team delivering to all major business domains.
- Drives ingestion and metadata service implementation for over 100 enterprise data sources.
- Collaborates across business IT, cybersecurity, infrastructure, and architecture teams to ensure secure and sustainable delivery.

Main Tasks

- Build and maintain Python- or Scala-based extraction services (e.g., Debezium Server, custom APIs, rclone)
- Implement CDC, delta, and event-based patterns.
- Push-based HTTP, Kerberos-authenticated DLT delivery.
- Establish, operate and troubleshoot extraction from SAP using tools like Theobald Extract Universal.o
- Integrate with systems such as Salesforce, SharePoint, and other API- or file-based endpoints.
- Establish and maintain a business-friendly, web-accessible data catalog application, with dataset profiles, metadata, and usability features.
- Integrate dataset discoverability, preview/exploration options, and lineage information using Unity Catalog as a backend metadata system.




- Design and implement structured access request workflows including request submission, approval chains, audit trail, and enablement triggers.
- Perform design reviews with Cybersecurity.
- Ensure documentation and compliance for all interfaces and data ingress points.
- Manage audit and traceability requirements.
- Collaborate closely with IT and business users to translate requirements into scalable technical patterns.
- Serve as technical escalation point for complex source integration.
- Define and implement a multi-layered data quality framework, including unit-level, integration-level, and cross-pipeline validation rules.
- Establish centralized and version-controlled storage of DQ rules, with integration into orchestration and CI/CD pipelines.
- Implement automatic DQ monitoring with severity levels (Critical, High, Medium, Low) and enable flagging, filtering, and quarantining logic at relevant stages of the pipeline.
- Collaborate with source system owners and business stakeholders to define meaningful and actionable DQ thresholds.

Required Skills

- Degree in Computer Science, Data Engineering, or a related field. Azure or Databricks certification is a plus.
- 5–8 years in data engineering, with hands-on experience in ingesting structured and unstructured enterprise data into contemporary cloud platforms.
- Proven implementation of source system ingestion frameworks, metadata automation, and compliance-controlled interfaces.
- Not required; however, experience mentoring junior developers or leading implementation workstreams is a plus; contributes to engineering standards and code quality improvement initiatives
- Comfortable working across geographies and time zones; collaborates effectively with global teams and enterprise stakeholders.

📌 Data Engineer (Bengaluru)
🏢 Continental
📍 Bengaluru