Data Engineer, 10-15 years

Celestica

Data Engineer designing and delivering data solutions enabling AI and advanced analytics. Leading end-to-end data lifecycle management and developing ETL pipelines at Celestica.

Posted 7/22/2026full-timeGuindy, Chennai • 🇮🇳 IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and delivering data solutions, managing the end-to-end data lifecycle, and implementing scalable ETL/ELT processes. Proficient in data manipulation, cleansing, and visualization using advanced tools and programming languages.

Highest-signal resume keywords

Data EngineeringETL/ELT Process ImplementationSQL ProficiencyPython AutomationPower BI or Tableau Expertise

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DevelopmentData Lake ArchitectureData CleansingData MappingMetadata ManagementData Catalogue MaintenanceComplex QueryingData ModelingPerformance TuningAPI Integration

Soft Skills

Requirement GatheringLifecycle Management

Tools & Technologies

Power BITableauPandasNumPy

Industry Keywords

Data SolutionsAdvanced AnalyticsData ValidationData Monitoring

Tech Stack

Tools & technologies

ETLNumpyPandasPythonSQLTableau

About the role

Key responsibilities & impact

Design and deliver robust data solutions that enable AI and advanced analytics across the organization.
Own the end-to-end data lifecycle: from requirement gathering and data mapping to implementing scalable pipelines.
Ingest data from disparate engineering and business tools into a single, curated, well-structured data lake and data catalogue.
Clean and curate complex datasets. Develop and maintain data catalogues, metadata, and data mapping documentation.
Architect, implement, and optimize scalable ETL/ELT processes, moving data from diverse sources.
Leverage Python to automate data validation, monitoring, and repetitive workflows.
Design and implement dashboards and reports using platforms like Power BI or Tableau to provide actionable insights.

Requirements

What you’ll need

8 to 10 years of hands-on experience in data engineering or closely related roles.
Proven experience building high-performance data pipelines and implementing end-to-end data solutions in a production environment.
Hands-on experience designing or operating a centralized data lake and data catalogue.
Strong coding skills for data manipulation (e.g., Pandas, NumPy), automation scripts, and API integrations.
Advanced skills in SQL for complex querying, data modeling, and performance tuning.
Hands-on experience in data cleansing, mapping, metadata management, and the creation/maintenance of data catalogues.
Professional-level experience with Power BI, Tableau, or similar BI platforms.
Demonstrated ability to lead requirement-gathering sessions and manage the lifecycle of data initiatives.

Benefits

Comp & perks

Health insurance
Professional development opportunities
Paid time off