Manager, Data & Integrations

10 - 12 years

10 - 12 Lacs

Posted:18 hours ago| Platform: Foundit logo

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Skills Required

Work Mode

On-site

Job Type

Full Time

Job 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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