Data Engineer

McCormick & Company; Gurugram District; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

McCormick & Company is searching for a Data Engineer in Gurugram District, Haryana. This role involves building scalable data pipelines and supporting business units with data needs. Candidates should have experience in data engineering, proficiency with PySpark, and a Bachelor's degree in a related field.

As a Data Engineer, you will engage in data modeling, ETL development, and ensure data quality. The position demands effective communication and the ability to manage priorities across multiple projects.

Qualifications

• 3-5 years of data engineering experience.
• Demonstrated ability coding in one or more languages, preferably PySpark.
• Experience with building data pipelines.

Responsibilities

• Collaborate with data product managers to gather data requirements.
• Implement and maintain ELT pipelines from various data sources.
• Assist stakeholders with data-related product pipeline issues.

Skills

Data pipeline building

PySpark

SQL performance tuning

Data modeling

ETL development

Education

Bachelor's degree in Mathematics, Statistics, Computer Science, Data Analytics/Science, or related field

Tools

Azure Synapse

APIs

SQL

Job description

At McCormick, we bring our passion for flavor to work each day. We encourage growth, respect everyone's contributions and do what's right for our business, our people, our communities and our planet.

Position Overview

As a 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 development, and ensuring data quality and security.

Key Responsibilities

• Execute: Collaborate with data product managers to gather data requirement; Execute ETL solutions including data security, data quality and performance requirements; Prepare documentation of data product lineage and all other related ETL topics.

• Data Extraction, Load and Transformation: Implement 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.

• Process Improvement, Performance and Cost optimization tuning: Collaborate 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.

• Issue Resolution and Support: Assist 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

• Experience

  • 3-5 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