Manager, Data - Bengaluru / Bangalore - confidential

    confidential
    confidential Bengaluru / Bangalore

    4 days ago

    Full time Healthcare
    Description

    In this role, you will:

    • Lead the data engineering team by driving the design, build, test, and launching of new data pipelines, data models, and predictive models on our production data platform
    • Lead a team of data engineers and guide them with the best data strategies in line with data needs
    • Identifying, designing, and implementing process improvements that include building/re-engineering data models, data architectures, pipelines, and data applications
    • Continuously look for data optimization processes and oversee data management, governance, security, and analysis
    • Hire the best talents, identify the potential of each team member and offer technical guidance, leadership, and advice on planning, designing, and implementing data solutions
    • Manage data delivery through high-performing dashboards, visualizations, and reports
    • Ensure data quality and security across every product vertical and related areas
    • Design, create and launch new data models and pipelines as per needs
    • Act as a project manager for data projects, mentor and grow the team by hiring skilled data engineers
    • Work towards achieving high performance, operational excellence, accuracy, and reliability of the overall system
    • Mentor and grow data warehouse, data modeling, and data visualization team to correctly establish a data-driven culture
    • Utilize tools and technologies to create data architecture that supports new data initiatives and is useful in next-gen products
    • Ensure test-driven products/pipelines that are easily maintainable and reusable
    • Design and build an infrastructure for extraction, transformation, and loading of data from a wide range of data sources
    • Overall build and maintain data foundations that include tools, infrastructure, and pipelines that help the marketing and sales team
    • Increase automation and build analytic solutions at scale to serve the business requirements

    Minimum requirements for the role:

    • Minimum 10+ years of experience in managing, designing, and maintaining large scale data and integration systems solutions
    • Bachelors degree in Computer Science, Math, Statistics, Information Systems, Informatics, Analytics, or another quantitative field
    • Hands-on experience analyzing, architecting/re-architecting data and analytics platforms on Azure/AWS/GCP
    • Must have experience designing and architecting data lakes on cloud platforms and BI tools/solution design.
    • Experience developing real time application integration for operational data integrations using tools such as Workato or Mulesoft or other relevant integration tools.
    • Experience developing or managing REST APIs
    • Programming knowledge and hands-on experience in Python.
    • Working knowledge of full software development life cycle that includes planning, coding standards, testing methods, build process, and source control management
    • Experience offering technical leadership and guiding teams for data engineering best practices
    • Strong knowledge of AWS tools and technologies

    An ideal candidate also has:

    • 10+ years of experience with very large scale data warehouse projects
    • Experience working with APIs to collect or ingest data.
    • Experience building APIs
    • Strong working knowledge of AWS Databricks, DBT and integration tools such as Workato.
    • Knowledge of data security best practices and experience building secure data solutions
    • Advanced working SQL knowledge and experience working with a variety of relational databases, query languages, query authoring, and related tools
    • Hands-on experience in building data pipelines, platforms, architecture, structures, visualizations, and data modeling
    • Optimize data models and conduct performance engineering for large scale data
    • Knowledge of data visualizations and self-service data preparation tools to maintain the flow of data for the analytics and visualization teams.
    • Experience working in a large-scale, high-scale data warehouse environment with ETL tools and processes
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