Data Engineer

Celebal Technologies; Mumbai, Navi Mumbai; On-site; INR 1,400,000 - 1,900,000; Full time

Job summary

Celebal Technologies is seeking a Data Engineer with 4+ years of experience to design and maintain ETL pipelines for retail data, integrating POS, CRM, ERP data, and external sources. You will build data warehouses and lakes, ensuring data quality and security while collaborating with data scientists and analysts.

Responsibilities include automating workflows with Airflow or dbt, supporting real-time analytics via Kafka/Spark Streaming, and applying governance best practices in a fast-growing

Qualifications

• 4+ years of experience as a Data Engineer, preferably in the retail or e-commerce domain.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• Strong programming skills in SQL, Python, or Scala.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Proficiency in data modeling, data warehousing, and ETL development.
• Understanding of retail KPIs like sales trends, customer segmentation, inventory turnover.

Responsibilities

• Design, develop, and maintain scalable ETL pipelines for retail data (sales, inventory, customer behavior).
• Integrate data from internal systems (POS, ERP, CRM) and external sources (market trends, vendor feeds).
• Build and manage data warehouses and data lakes using platforms like Snowflake, Redshift, or BigQuery.
• Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver solutions.
• Ensure data quality, integrity, and security across all data platforms.
• Implement data governance and compliance best practices.
• Automate data workflows and monitor pipeline health using tools like Apache Airflow, dbt, or Luigi.
• Support real-time analytics and streaming data using tools like Kafka or Spark Streaming.

Skills

SQL

Python

Scala

Data Modeling

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field

Tools

Snowflake

Redshift

BigQuery

Airflow

dbt

Kafka

Spark

Job description

About the Role:

We are seeking a skilled and detail-oriented Data Engineer with 4 years of experience, preferably in the retail sector, to join our growing data team. You will be responsible for building and maintaining robust data pipelines, integrating data from various retail systems (POS, CRM, ERP), and enabling data-driven decision-making across the organization

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines for retail data (sales, inventory, customer behavior).


• Integrate data from internal systems (e.g., POS, ERP, CRM) and external sources (e.g., market trends, vendor feeds)


• Build and manage data warehouses and data lakes using platforms like Snowflake, Redshift, or BigQuery.


• Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver solutions.


• Ensure data quality, integrity, and security across all data platforms.


• Implement data governance and compliance best practices.


• Automate data workflows and monitor pipeline health using tools like Apache Airflow, dbt, or Luigi.


• Support real-time analytics and streaming data using tools like Kafka or Spark Streaming.

Required Skills & Qualifications

• Bachelor?s or Master?s degree in Computer Science, Data Engineering, or related field.


• 4+ years of experience as a Data Engineer, preferably in the retail or e-commerce domain.


• Strong programming skills in SQL, Python, or Scala.


• Experience with cloud platforms (AWS, Azure, or GCP)


• Proficiency in data modeling, data warehousing, and ETL development.


• Understanding of retail KPIs like sales trends, customer segmentation, inventory turnover, etc.


• Excellent problem-solving, communication, and collaboration skills.


• Optimize query performance and data retrieval for reporting and analytics.

Preferred

• Experience with CI/CD pipelines, version control (Git), and DevOps practices


• Exposure to machine learning pipelines or recommendation systems in retail.


• Knowledge of data visualization tools like Power BI, Tableau, or Looker