Senior Data Engineer

McCormick & Company · Gurgaon

  • Experience5–8 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Posted24 Sept 2026
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About McCormick & Company

McCormick & Company is hiring in Gurgaon in agriculture food. This role looks for around 5+ years of experience.

Skills

  • PySpark
  • Azure Synapse
  • SQL
  • Databricks
  • Azure Data Factory
  • Azure Data Engineering
  • Data pipelines
  • ETL
  • ELT
  • Data modeling
  • Data quality
  • Data security
  • Structured data
  • Semi-structured data
  • Unit testing
  • Git
  • Medallion architecture
  • Data privacy
  • Azure DevOps
  • CI/CD

The role

A data engineer at a food manufacturing company builds scalable data products and pipelines for analytics and AI using PySpark, Azure Synapse, and Databricks, while improving data quality and performance. The role also applies SQL performance tuning and Azure Data Factory to deliver reliable datasets for business stakeholders.

Full job description

Position Overview

As a Senior Data Engineer at McCormick, you will play a pivotal role in the build and delivery of data products from simple to complex and supporting McCormick business units with their data and analytics needs.Your responsibilities will include delivering and supporting data for existing analytics solutions, tooling, and solutions, researching new features and implementing automations. You will support business users, Data Scientists and Data Analysts to convert business expectations into data products and data models usable by business to deliver AI, analysis, reporting, and data-driven recommendations to stakeholders and executives.This role will be accountable for building and maintaining scalable data pipelines from source systems. The Data Engineer will ensure the availability, reliability, and performance of data products by integrating raw data from various sources. Key responsibilities include data modeling, ETL (Extract, Transform, Load) development, and ensuring data quality and security. This role will be accountable for data coming in from 1-3 source systems.

Key Responsibilities

1. ExecuteCollaborate with data product managers to gather data requirementExecute ETL solutions including data security, data quality and performance requirements.Prepare documentation of data product lineage and all other related ETL topics.

2. Data Extraction, Load and TransformationImplement and maintain ELT pipelines to efficiently ingest and transform data from a wide variety of data sources and deliver datasets that meet business requirements.Ensure efficient and reliable data mapping to support business needs.Deliver complete documentation and knowledge transfer sessions for the Team and business partners.Maintain existing solutions, implement optimizations and enhancements, monitor data quality.Support the development and maintenance of scalable data pipelines leveraging Azure Synapse, PySpark, APIs, and SQL & performing advanced data cleaning, transformation, and manipulation to ensure high-quality, and reliable data flows.

3. Process Improvement, Performance and Cost optimization tuningCollaborate with Data Science, AI, and Data product teams to optimize performance and cost effectiveness of their solutions.Identify and support the design of internal process improvements, including automating manual processes, optimizing data product delivery, and redesigning solutions for enhanced scalability.Implement solution adjustments to improve performance and cost-effectiveness of data products.

4. Issue Resolution and SupportAssist stakeholders with data-related product pipeline issues and support their data product needs.Work with the Analytics Operational Support team to investigate, troubleshoot, and resolve data errors / discrepancies.

Required Qualifications:

Level of Education and Discipline Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Analytics/Science, or related field

Certifications and/or Licenses Microsoft Certified: Azure Data Engineer Associate (DP-900) or Microsoft Certified: Fabric Data Engineer Associate or related cloud technologies, Fabric IQ/databricks certifications a plus

Experience5-8 years of data engineering experience.Demonstrated ability coding in one or more languages (PySpark preferred).Experience with building data pipelines.Demonstrated ability to manage multiple priorities simultaneously.Basic SQL performance tuning.Structured + semi-structured data handling.Unit testing for pipelines.Git-based workflow.Exposure to medallion architecture.Understanding of data privacy basics.

Interpersonal Skills Effective communication skills and ability to communicate effectively on technical and business issues both internally and externally.Ability to work independently, navigate problems, resolve conflicts, and bring solutions to the table.Build strong interpersonal relationshipsTime management and prioritization skillsStrong technical curiosity and passion for problem solving and innovationOngoing aspiration to learn about new industry tools

Other Skills & Competencies Knowledge of data analysis, visualization techniques, and frameworks.Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.Experience with the following tooling:SQL, Fabric, Databricks, Synapse, Azure Data Factory, Azure ML, Azure DevOps (for CI/CD), OR (Secondary)GCP BigQuery, FiveTran, GCP Cloud Composer, GCP DLP (Data Loss Prevention), GCP Cloud Run, Vertex AI etc