Capabilities & Insights Analyst

• 6+ years of data science experience.

• Demonstrated experience in leading programs.

• Prior experience in customer data platforms/finance domain is a plus.

• Demonstrated ability in developing and deploying data-driven products.

• Experience of working with large datasets and developing scalable algorithms.

• Hands-on experience of working with tech, product, and operation teams.

Technical Skills:

• Deep understanding and hands-on experience of Machine learning and Deep

learning algorithms. Good understanding of NLP and LLM concepts and fair

experience in developing NLU and NLG solutions.

• Experience with Keras/TensorFlow/PyTorch deep learning frameworks.

• Proficient in scripting languages (Python/Shell), SQL.

• Good knowledge of Statistics.

• Experience with big data, cloud, and MLOps.

Soft Skills:

• Strong analytical and problem-solving skills.

• Excellent presentation and communication skills.

• Ability to work independently and deal with ambiguity.

Continuous Learning:

• Stay up to date with emerging technologies.

Qualification.

A degree in Computer Science, Statistics, Applied Mathematics, Machine Learning, or any related field / B. Tech.

Designation – Deputy Manager - TS

Job Description

1. Total of  8/9 years of development experience Data Engineering . B1/BII role
2. Minimum of 4/5 years in AWS Data Integrations and should be very good on Data modelling skills.
3. Should be very proficient in end to end AWS Data solution design, that not only includes strong data ingestion, integrations (both Data @ rest and Data in Motion) skills but also complete DevOps knowledge.
4. Should have experience in delivering at least 4 Data Warehouse or Data Lake Solutions on AWS.
5. Should be very strong experience on Glue, Lambda, Data Pipeline, Step functions, RDS, CloudFormation etc.
6. Strong Python skill .
7. Should be an expert in Cloud design principles, Performance tuning and cost modelling. AWS certifications will have an added advantage
8. Should be a team player with Excellent communication and should be able to manage his work independently with minimal or no supervision.
9. Life Science & Healthcare domain background will be a plus

Qualifications

BE/Btect/ME/MTech

• Creating and managing ETL/ELT pipelines based on requirements
• Build PowerBI dashboards and manage datasets needed.
• Work with stakeholders to identify data structures needed for future and perform any transformations including aggregations.
• Build data cubes for real-time visualisation needs and CXO dashboards.

Required Tech Skills

• Microsoft PowerBI & DAX
• Python, Pandas, PyArrow, Jupyter Noteboks, ApacheSpark
• Azure Synapse, Azure DataBricks, Azure HDInsight, Azure Data Factory

• Be the analytical expert in Kaleidofin, managing ambiguous problems by using data to execute sophisticated quantitative modeling and deliver actionable insights.
• Develop comprehensive skills including project management, business judgment, analytical problem solving and technical depth.
• Become an expert on data and trends, both internal and external to Kaleidofin.
• Communicate key state of the business metrics and develop dashboards to enable teams to understand business metrics independently.
• Collaborate with stakeholders across teams to drive data analysis for key business questions, communicate insights and drive the planning process with company executives.
• Automate scheduling and distribution of reports and support auditing and value realization.
• Partner with enterprise architects to define and ensure proposed.
• Business Intelligence solutions adhere to an enterprise reference architecture.
• Design robust data-centric solutions and architecture that incorporates technology and strong BI solutions to scale up and eliminate repetitive tasks.

• Experience leading development efforts through all phases of SDLC.
• 2+ years "hands-on" experience designing Analytics and Business Intelligence solutions.
• Experience with Quicksight, PowerBI, Tableau and Qlik is a plus.
• Hands on experience in SQL, data management, and scripting (preferably Python).
• Strong data visualisation design skills, data modeling and inference skills.
• Hands-on and experience in managing small teams.
• Financial services experience preferred, but not mandatory.
• Strong knowledge of architectural principles, tools, frameworks, and best practices.
• Excellent communication and presentation skills to communicate and collaborate with all levels of the organisation.
• Preferred candidates with less than 30 days notice period.

1. Create and maintain optimal data pipeline architecture
2. Assemble large, complex data sets that meet business requirements
3. Identifying, designing, and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes
4. Work with Data, Analytics & Tech team to extract, arrange and analyze data
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
6. Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
7. Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
8. Working with stakeholders including data, design, product, and executive teams, and assisting them with data-related technical issues
9. Working with stakeholders including the Executive, Product, Data, and Design teams to support their data infrastructure needs while assisting with data-related technical issues.

1. SQL
2. Ruby or Python(Ruby preferred)
3. Apache-Hadoop based analytics
4. Data warehousing
5. Data architecture
6. Schema design
7. ML

1.  Prior experience of 2 to 5 years as a Data Engineer.
2. Ability in managing and communicating data warehouse plans to internal teams.
3. Experience designing, building, and maintaining data processing systems.
4. Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions.
5. Excellent analytic skills associated with working on unstructured datasets.
6. Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.

We are actively seeking a Senior Data Engineer experienced in building data pipelines and integrations from 3rd party data sources by writing custom automated ETL jobs using Python. The role will work in partnership with other members of the Business Analytics team to support the development and implementation of new and existing data warehouse solutions for our clients. This includes designing database import/export processes used to generate client data warehouse deliverables.