Key critical skills required for this role include:
- A large part of this role will be On-going support and enhancement to Warehouse, Reporting, Information management and its design, Dashboard Creation, Maintenance, Automation, Data Set Curation, Data Set Transformation.
- Given the high exposure to Data, Reporting, Warehouses, Dashboards, this role will be governed by Service Level Agreements and will be responsible for adherence to Data Standards, and Timelines.
- Delivering in-sights to enable earlier, faster, smarter decisions. This will rely on some Stake-holder management, partnership, building relationships. Another key factor will be the ability to present and articulate a value proposition.
- Act as a data/technical expert for warehouses and tools used within the department, providing, support to colleagues.
- Provide guidance to the rest of the team on all issues relating to data sources.
- Through extensive knowledge of python, pyspark and/or SQL, provide guidance to other team members on all aspects of coding, including efficiency and effectiveness.
- Be a Subject Matter Expert, and support colleagues in other appropriate teams by sharing knowledge & best practices in coding and data.
- Currently this role is intended to be an Individual Contributor, however, this can evolve over time.
- Graduate in any discipline.
- Ability to work dedicated shifts in the range of 12 Noon IST to 12 AM IST.
- Minimum 6 Years experience in Data Science Domain (Analytics and Reporting).
- Ability to write and study and correct Python, SQL code is mandatory.
- Ability to work with Big Data.
You may be assessed on key essential skills relevant to succeed in role, such as strong knowledge on Python, SQL, Big Data, Power BI, Tableau strategic thinking as well as job-specific technical skills.
This role is based out of our Noida office.
Purpose of the role
To implement data quality process and procedures, ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organisation improve its operation, and optimise resources.
Accountabilities
- Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification.
- Execution of data cleansing and transformation tasks to prepare data for analysis.
- Designing and building data pipelines to automate data movement and processing.
- Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems.
- Documentation of data quality findings and recommendations for improvement.