Acknowledger

Lead Data Engineer

bengaluru / bangalore
SEP 22 2024

closes 30 Oct 2024

job details

  • Acknowledger First Pvt Ltd
  • permanent

Bachelor of Engineering

Job code
AFPL/VeARC/LDE003

Job Description:

We are seeking a highly skilled Senior Data Engineer to lead and execute our data strategy preferably experienced in Financial Services/Procurement domain, to build a modern data ingestion and data analytics platform using latest technologies like AWS Athena, Lambda, Python, Spark and PowerBI. This role is critical to ensuring that our product remains at the forefront of innovation, enabling better decision-making and enhanced customer experiences through data-driven insights. You will work closely with cross-functional teams to design, build, and maintain scalable data pipelines and systems, ensuring seamless integration with various data sources and applications.

 

Apply to:
hr@acknowledgerfirst.com

  • Must Have:

    Expert – Python, Shell Script, AWS Redshift, S3, Lambda, Postgres, Apache Kafka, AWS Glue/Spark, Data Modelling

    Significant work Experience – Jenkins, Power BI, Data Monitoring (Data dog)

     

    Good to have: Model Ops

  • Data Strategy Development: Collaborate with leadership to define and implement a comprehensive data strategy that aligns with our business
  • Data Pipeline Management: Design, develop, and maintain robust, scalable data pipelines that collect, process, and analyze data from multiple sources including AWS, Salesforce, and
  • Data Modeling: Develop and maintain logical, conceptual, and physical data models that ensure data is structured and organized effectively to support business processes and
  • ETL Development: Create and optimize ETL processes to ensure efficient data integration, transformation, and
  • Database Management: Oversee the architecture and management of databases (Postgres) to ensure data integrity, availability, and
  • Analytics Enablement: Work closely with data analysts and data scientists to provide clean, well- organized data sets for analysis, reporting, and machine learning
  • Automation: Implement automation solutions to streamline data processing tasks, reduce manual effort, and enhance operational efficiency.