Senior Data Solutions Architect

2 weeks ago

Morādābād, Uttar Pradesh, India beBeeDataEngineering Full time ₹ 7,50,000 - ₹ 12,50,000

Transforming the Food and Beverage Industry with Data Engineering

We are a leading provider of unified commerce platforms, delivering cutting-edge software solutions for the global food industry.

Our team of passionate developers, designers, and product experts is constantly evolving—introducing innovative features that set the benchmark for F&B tech.

We're on a mission to revolutionize the F&B industry with our powerful cloud-based POS and restaurant management platform.

As part of our growing data team, you'll collaborate closely with developers, architects, analysts, and data scientists to ensure smooth, secure, and efficient data delivery across multiple products and projects.

We offer a platform to explore, apply, and grow your skills in modern data engineering.

  • Design, build, and maintain scalable data pipelines and infrastructure.
  • Assemble and manage large, complex datasets from diverse sources.
  • Automate and optimize data processes for greater efficiency and scalability.
  • Develop and manage ETL workflows using SQL and cloud-based big data tools.
  • Build analytics tools to deliver actionable insights into business performance.
  • Collaborate with executives, product managers, architects, and analysts to meet evolving data needs.
  • Ensure data systems are secure, reliable, and high-performing.
  • Support data scientists and analysts by creating data tools and environments for advanced analytics.

You'll have opportunities to work on high-impact projects shaping the future of the F&B tech industry.

What We Look For:

  • 2–7 years of hands-on experience as a Data Engineer.
  • A graduate degree in Computer Science, IT, Statistics, or a related quantitative field.
  • Advanced knowledge of SQL and relational databases, with exposure to multiple database technologies.
  • Proven experience building and optimizing big data pipelines, architectures, and data sets.
  • Strong analytical skills, especially in handling unstructured datasets.
  • Working knowledge of cloud-based big data services (AWS, Azure, or GCP).
  • Familiarity with big data tools such as Hadoop, Spark, Kafka, etc.
  • Experience with ETL tools like Informatica, DataStage, or Azure Data Factory.
  • Knowledge of stream-processing systems like Storm or Spark Streaming.
  • Proficiency in scripting/programming languages such as Python, Java, or Scala.
  • Excellent communication skills and the ability to thrive in cross-functional teams.

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