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Job Location: Bangalore/Bengaluru
Designation
Data Analysis Lead
Department
Modelling and Data analysis
Reporting to
Head of department
Work Location
Bangalore
Minimum Qualification
Bachelor’s degree in computer science/ information technology, / applied math.
B.Tech with data engineering certifications like IBM Certified Data Engineer or Google’s Certified Professional in data science
Special expertise
- Good understanding of DATA STRUCTURERS, Statistics & Mathematics
Experience in Years
- 4 to 5 years
Additional skill set -Software knowledge
- Strong Programming Skills
- Understanding Machine learning and its integration with Data engineering.
- Scripting knowledge to extract data from database
Mandatory requirements
- Experience with relational SQL and NoSQL databases
- Experience with object-oriented/object function scripting languages: Python, Java, C++, etc
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Basic understanding of fundamental algorithms – searching, sorting, trees graphs, etc
- Hands on experience in Data formatting (type conversion), data transformation (joining , slicing, indexing) and handling missing data
- Experience in building ETL pipeline, strong Programming skills, working on cloud services, and deploying ML model in production
- Experience in Data Visualization using relevant libraries of Python & building dashboards using Tableau
Target Companies
- Premier school with Data Science as specialisation
- Data engineering companies. (Intuit , netapp , Capgemini etc )
Strategic Accountability / Responsibilities
- Create and maintain optimal data pipeline architecture,
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product development teams to assist with data-related technical issues and support data infrastructure needs.
- Work with data and analytics experts to strive for greater functionality in our data systems
Operational Accountability / Responsibilities
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL / NoSQL and database management technologies.
- Identify, design, and implement automating manual processes, optimizing data delivery, designing infrastructure for greater scalability.
- Create data tools for analytics and data scientist team members that assist them in building product
Internal interface
- Cross functional teams
- Heads of all Departments
- All Employees
External interface
- Data engineering Communities
- Industrial associations/ professional forums
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