Algotale Group (Netscribes ) - Data Analyst – Information Technology

Company- Algotale ( Netscribes )

Position - Data Analyst – Information Technology

YOE- 1-4 Years

Function: Information Technology

Location- Pune, Maharashtra

Job Summary

• Analyzes and interprets data to drive strategic business decisions and improve data utilization
• across the organization. Collaborates with business stakeholders to gather requirements,
• identify patterns and trends, and provide actionable insights. Prepares comprehensive reports
• for senior leadership, champions the enhancement of data quality and processes, and
• contributes to technology-driven initiatives within analytics to align with organizational
• objectives. Utilizes current market tools like Microsoft PowerBI, Microsoft SSIS, SAP Reporting
• (Fiori App), SAP Datasphere, and SAP Analytics Cloud to design, develop, and deliver
• advanced reporting and analytics solutions that support organizational goals.

Key Responsibilities

•  Conducts descriptive and diagnostic analytics on data sources, review results with
• senior leadership, and takes required actions but not limited to using tools such as SAP
• Reporting (Fiori App) and SAP Analytics Cloud.
•  Applies machine learning and machine learning tools on data and metadata to improve
• data quality and provides recommendations and designs solutions to resolve issues, and
• can program in tools such python.
•  Identifies patterns and trends in data sets; applies statistical process controls on data,
• and can utilise tools such python to support these analysis.
•  Creates complex data model to support reports and dashboards, to provide curated data
• for analysis results, leveraging advanced capabilities of Microsoft PowerBI, SAP Analytic
• Cloud, and other business intelligence tools and technologies.
•  Develops data profiles for data schemas, tables, and elements in RDBMS or in our
• Snowflake data lake.
•  Creates and evaluates data catalogue entries, ensures data catalogue metadata quality,
• and leverages data catalogue information to provide guidance to product development
• teams.
•  Analyzes complex and diverse data sets from multiple sources to identify data quality,
• coherency and integrability issues and reduce data redundancy; provides
• recommendations to resolve issues throughout the data lifecycle.
•  Collaborates to develop data cleansing methods and rules, and the use of AI
• technologies to support the delivery of these methods and rules.
•  Assists in creation and maintenance of documentation of key decisions, rules, controls,
• processes and training material with the use of AI technologies.
•  Collaborates to integrate data analysis findings into governance solutions.
•  Defines new methods and integrates new tools, such as CoPilot, ChatGPT, Microsoft
• Fabric, SAP Analytics Cloud, and other tools, into data analysis processes.
•  Coaches, mentors and reviews work of less experienced team members and provides
• guidance on problem resolution.
•  Monitor and measure project outcomes and ensure continuous improvement of
• execution processes

Competencies

•  Data Literacy - Expresses data in context, including data sources and constructs,
• analytical methods and applied techniques; describes the use-case application and
• resulting value.
•  Data Profiling - Assesses data issues and cleansing requirements to perform data
• extraction, mapping, collection, and testing; establishes good, quality data.
•  Data Communication and Visualization - Constructs a tale of the business problem,
• root cause, solution options, and opportunities through illustrating data visually, including
• reports and dashboards created in SAP Analytics Cloud.
•  Data Quality - Identifies, understands and corrects flaws in data that supports effective
• information governance across operational business processes and decision making.
•  Project Management - Establishes and maintains the balance of scope, schedule and
• resources for a temporary effort (a "project").
•  Data Analytics - Discovers, interprets and communicates qualitative and quantitative
• data; determines conclusions relying on knowledge of business or functional
• frameworks; simultaneously applies statistics, data validity, data visualization, and
• problem-solving approaches to effectively extract meaningful patterns and business
• insights using tools such as SAP Reporting (Fiori App) and SAP Analytics Cloud;
• presents conclusions and outcomes that enable data driven business decisions.
•  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.
•  Tech savvy - Anticipating and adopting innovations in business-building digital and
• technology applications. Have strong background in AI development and use.
•  Balances stakeholders - Anticipating and balancing the needs of multiple stakeholders.
•  Action oriented - Taking on new opportunities and tough challenges with a sense of
• urgency, high energy, and enthusiasm.
•  Manages ambiguity - Operating effectively, even when things are not certain or the way
• forward is not clear.

Education, Licenses, Certifications

• 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.

Experience

• Intermediate experience in a relevant discipline is required. Knowledge of the latest
• technologies and trends in data science is highly preferred and includes the following

MANDATORY and OPTIONAL skills

• MANDATORY - SQL query language execution on NOSql and SQL sources
• MANDATORY - Python language
• MANDATORY - Exposure to Agile software development
• OPTIONAL - Exposure to IoT technology
• MANDATORY - Experience with AI tools; ChatGPT, and CoPilot.
• OPTIONAL - Experience with AI tools; AgentForce, SAP Joule, Sineque, and others.
• OPTIONAL - Data profiling tools, technologies and coding
• OPTIONAL - Data Modelling tools, technologies and coding
• OPTIONAL - Data Governance tools, technologies and coding
• OPTIONAL - Data Catalog tools and technologies
• MANDATORY - Business intelligence tools and technologies

Intermediate experiences in the following are PREFERRED

• Exposure to Big Data open source
• Exposure to Machine Learning open source
• Exposure to Docker and Kubernetes open source
• Clustered compute cloud-based implementation experience