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
