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Req ID: 139673
Remote Position: Hybrid
Region: Asia
Country: India
State/Province: Chennai
City: Guindy, Chennai

General Overview

Functional Area: Engineering
Career Stream: Design - Software Engineering
SAP Short Name: ENG-ENG-DSE
Job Level: Level 07
IC/MGR: Individual Contributor
Direct/Indirect Indicator: Indirect

Summary

The Data Engineer will play a key role in designing and delivering robust data solutions that enable AI and advanced analytics across the organization. This role owns the end‑to‑end data lifecycle: from requirement gathering and data mapping to implementing scalable pipelines, managing metadata, and creating high‑level reporting visualizations.

A primary focus of this role is to ingest data from disparate engineering and business tools into a single, curated, well‑structured data lake and data catalogue. The engineer will transform raw, fragmented data into curated, high‑quality datasets from multiple source platforms, so that data scientists can easily discover datasets in the catalogue and export them in table format for modeling and analytics.

Detailed Description

• Requirement Management: Facilitate deep‑dive sessions with business and technology leaders to gather and manage technical requirements, ensuring data initiatives align with strategic organizational goals.
• Data Ingestion & Integration: Design and implement connectors and ingestion jobs that pull data from multiple tools (e.g., Azure DevOps, Jira, test systems, logs) into the central data lake.
• Data Curation, Metadata Management & Governance: Lead efforts to clean and curate complex datasets. Develop and maintain data catalogues, metadata, and data mapping documentation to ensure transparency, lineage, and trust across the ecosystem.
• End‑to‑End Pipeline & ETL Development: Architect, implement, and optimize scalable ETL/ELT processes, moving data from diverse sources into enterprise‑grade data lake and warehouse environments.
• Automation & Python Scripting: Leverage Python to automate data validation, monitoring, and repetitive workflows, improving the efficiency and reliability of the data ecosystem.
• Advanced Analytics & Visualization: Design and implement dashboards and reports using platforms like Power BI or Tableau to provide actionable insights to stakeholders at all levels.
• Data Integrity & Security: Implement rigorous data quality checks, monitoring, and security controls to maintain accuracy, compliance, and “gold‑standard” data health.
• Cross‑Functional Collaboration: Partner with data scientists and other teams to understand their access patterns, ensure datasets are documented and queryable, and streamline export of curated tables for downstream ML and analytics.

Knowledge/Skills/Competencies

Mandatory Skills and Qualifications

• Experience: 4 to 8 years of hands‑on experience in data engineering or closely related roles.
• Data Engineering & Solutions: Proven experience building high‑performance data pipelines and implementing end‑to‑end data solutions in a production environment.
• Data Lake & Data Catalogue Experience: Hands‑on experience designing or operating a centralized data lake and data catalogue, including dataset onboarding, partitioning, and access patterns for analytics and ML.
• Python Proficiency: Strong coding skills for data manipulation (e.g., Pandas, NumPy), automation scripts, and API integrations.
• SQL Mastery: Advanced skills in SQL for complex querying, data modeling, and performance tuning.
• Data Curation & Metadata Management: Hands‑on experience in data cleansing, mapping, metadata management, and the creation/maintenance of data catalogues.
• Visualization Mastery: Professional‑level experience with Power BI, Tableau, or similar BI platforms to create compelling, user‑centric data stories.
• Requirement Management: Demonstrated ability to lead requirement‑gathering sessions and manage the lifecycle of data initiatives with both technical and non‑technical stakeholders.

Preferred Qualifications

• Cloud & DevOps: Familiarity with major cloud platforms (Azure, GCP) and CI/CD practices for data applications using tools like Git.
• AI Support: Experience preparing and managing data specifically for machine learning models and AI‑driven analytics (e.g., feature engineering, labeling, dataset versioning).

Physical Demands

• Duties of this position are performed in a normal office environment.
• Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data.
• Repetitive manual movements (e.g., data entry, using a computer mouse, using a calculator, etc.) are frequently required.
• Occasional travel may be required.

Typical Experience

4 to 8 years

Typical Education

Bachelor degree or consideration of an equivalent combination of education and experience.

Educational Requirements may vary by Geography

Notes

This job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.

Celestica is an equal opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on any protected status (including race, religion, national origin, gender, sexual orientation, age, marital status, veteran or disability status or other characteristics protected by law).
At Celestica we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. Special arrangements can be made for candidates who need it throughout the hiring process. Please indicate your needs and we will work with you to meet them.

COMPANY OVERVIEW:

Celestica, Inc. (NYSE: CLS; TSX: CLS) is a technology leader dedicated to driving customer success and market advancements. With deep expertise in design, engineering, manufacturing, supply chain, and platform solutions, Celestica enables critical data center infrastructure for AI, cloud, and hybrid cloud and advances technologies in high-growth markets. With a talented team and a strategic global network, Celestica helps its customers achieve competitive advantages.

Today, Celestica delivers innovative supply chain solutions globally to customers in strategic two operating and reporting segments: Advanced Technology Solutions (ATS) and Connectivity and Cloud Solutions (CC):

ATS: This segment serves customers in complex, regulated and high-reliability markets such as Industrial & Smart Energy, Aerospace & Defense, Semiconductor Capital Equipment, and HealthTech. It is engineering led, with deep expertise in design, manufacturing and lifecycle solutions.

CCS: This segment focuses on high-performance technology solutions and services for the data center, serving hyperscalers, digital native customers and enterprises. Celestica's Platform Solutions offering provides innovative and customizable computing, storage and networking solutions enabling AI-driven growth.

Built on a legacy of trust and performance, Celestica has earned its reputation by delivering results in complex and fast-changing markets. Celestica exceeds customer expectations by identifying trends and staying ahead of the curve. Backed by comprehensive capabilities and a global network across North America, Europe and Asia, Celestica helps customers gain competitive advantage with the quality, flexibility and resiliency they need to respond quickly to shifts in demand. Guided by a bold vision to accelerate market advancements, Celestica delivers innovative solutions and technologies that turn complexity into opportunity. Anchored in teamwork and commitment, Celestica strives to be the most trusted partner to its customers and colleagues worldwide.

Celestica would like to thank all applicants, however, only qualified applicants will be contacted.
Celestica does not accept unsolicited resumes from recruitment agencies or fee based recruitment services.