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Data Analytics Team Leader

Data Analytics Team Leader

ConfidentialPune
30+ days ago
Job description

Key Responsibilities :

  • Facilitate data, compliance, and environment governance processes for the assigned domain.
  • Lead analytics projects to produce insights for the business to improve decision making, delivering results using reports, business intelligence technology, or other appropriate mechanisms.
  • Integrate data analysis findings into governance solutions.
  • Ingest key data for assigned domain into the data lake, ensuring creation and maintenance of relevant metadata and data profiles.
  • Coach team members, business teams, and stakeholders to find necessary and relevant data when needed.
  • Contribute to relevant communities of practice promoting the responsible use of analytics.
  • Develop the capability of peers and team members to operate within the Analytics Ecosystem.
  • Mentor and review work of less experienced peers and team members, providing guidance on problem resolution.
  • Integrate data from warehouse, data lake, and other source systems to build models for use by the business.
  • Cleanse data to ensure accuracy and reduce redundancy.
  • Lead preparation of communications to leaders and stakeholders.
  • Design and implement data / statistical models.
  • Collaborate with stakeholders to drive analytics initiatives.
  • Automate complex workflows and processes using Power Automate and Power Apps.
  • Manage version control and collaboration using GITLAB.
  • Utilize SharePoint for extensive project management and data collaboration.
  • Regularly update work progress via JIRA / Meets (also to stakeholders).

External Qualifications and Competencies

Qualifications :

  • College, university, or equivalent degree in relevant technical discipline, or relevant equivalent experience required.
  • This position may require licensing for compliance with export controls or sanctions regulations.

    • Competencies :

  • Balances stakeholders : Anticipating and balancing the needs of multiple stakeholders.
  • Collaborates : Building partnerships and working collaboratively with others to meet shared objectives.
  • Communicates effectively : Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
  • Customer focus : Building strong customer relationships and delivering customer-centric solutions.
  • Manages ambiguity : Operating effectively, even when things are not certain or the way forward is not clear.
  • Organizational savvy : Maneuvering comfortably through complex policy, process, and people-related organizational dynamics.
  • Data Analytics : Discovering, interpreting, and communicating qualitative and quantitative data; determining conclusions relying on knowledge of business or functional frameworks; simultaneously applying statistics, data validity, data visualization, and problem-solving approaches to effectively extract meaningful patterns and business insights; presenting conclusions and outcomes that enable data-driven business decisions.
  • Data Mining : Extracting insights from data by identifying relationships and patterns through use of a suite of data exploration and data visualization techniques to understand the underlying structure of the data and enable sound conclusions upon model building.
  • Data Modeling : Creating, writing, and testing data models, test scripts, and build scripts using industry standards and tools, version control, and build and test automation to meet business, technical, security, governance, and compliance requirements.
  • Data Communication and Visualization : Constructing a tale of the business problem, root cause, solution options, and opportunities through illustrating data visually, including reports and dashboards.
  • Data Literacy : Expressing data in context, including data sources and constructs, analytical methods, and applied techniques; describing the use-case application and resulting value.
  • Data Profiling : Assessing data issues and cleansing requirements to perform data extraction, mapping, collection, and testing; establishing good, quality data.
  • Data Quality : Identifying, understanding, and correcting flaws in data that supports effective information governance across operational business processes and decision making.
  • Project Management : Establishing and maintaining the balance of scope, schedule, and resources for a temporary effort (a project). Ensuring results / impact from temporary effort are fully realized as possible.
  • Values differences : Recognizing the value that different perspectives and cultures bring to an organization.

    • Additional Responsibilities Unique to this Position

    Technical Skills :

  • Advanced Python
  • Databricks, Pyspark
  • Advanced SQL, ETL tools
  • Power Automate
  • Power Apps
  • SharePoint
  • GITLAB
  • Power BI
  • Jira
  • Mendix
  • Statistics

    • Soft Skills :

  • Strong problem-solving and analytical abilities.
  • Excellent communication and stakeholder management skills.
  • Proven ability to lead a team.
  • Strategic thinking
  • Advanced project management

    • Experience :

  • Intermediate level of relevant work experience required.
  • Please note that this is a Hybrid role

    • Role :   Analytics Consultant

    Industry Type :   Industrial Equipment / Machinery

    Department :   Data Science & Analytics

    Employment Type :   Full Time, Permanent

    Role Category :   Business Intelligence & Analytics

    Education

    UG :   Any Graduate

    PG :   Any Postgraduate

    Skills Required

    Pyspark, Data Modeling, Power Apps, Power Automate, Data Mining, Sql, Data Quality, Project Management, Databricks, Data Analytics, Python, Etl

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