11+ Data modeling Jobs in Mumbai | Data modeling Job openings in Mumbai

Minimum of 8 years of experience of which, 4 years should be of applied data mining

experience in disciplines such as Call Centre Metrics.

 Strong experience in advanced statistics and analytics including segmentation, modelling, regression, forecasting etc.

 Experience with leading and managing large teams.

 Demonstrated pattern of success in using advanced quantitative analytic methods to solve business problems.

 Demonstrated experience with Business Intelligence/Data Mining tools to work with

data, investigate anomalies, construct data sets, and build models.

 Critical to share details on projects undertaken (preferably on telecom industry)

specifically through analysis from CRM.

Lifespark is looking for individuals with a passion for impacting real lives through technology. Lifespark is one of the most promising startups in the Assistive Tech space in India, and has been honoured with several National and International awards. Our mission is to create seamless, persistent and affordable healthcare solutions. If you are someone who is driven to make a real impact in this world, we are your people.

Lifespark is currently building solutions for Parkinson’s Disease, and we are looking for a ML lead to join our growing team. You will be working directly with the founders on high impact problems in the Neurology domain. You will be solving some of the most fundamental and exciting challenges in the industry and will have the ability to see your insights turned into real products every day

Essential experience and requirements:

1. Advanced knowledge in the domains of computer vision, deep learning

2. Solid understand of Statistical / Computational concepts like Hypothesis Testing, Statistical Inference, Design of Experiments and production level ML system design

3. Experienced with proper project workflow

4. Good at collating multiple datasets (potentially from different sources)

5. Good understanding of setting up production level data pipelines

6. Ability to independently develop and deploy ML systems to various platforms (local and cloud)

7. Fundamentally strong with time-series data analysis, cleaning, featurization and visualisation

8. Fundamental understanding of model and system explainability

9. Proactive at constantly unlearning and relearning

10. Documentation ninja - can understand others documentation as well as create good documentation

Responsibilities :

1. Develop and deploy ML based systems built upon healthcare data in the Neurological domain

2. Maintain deployed systems and upgrade them through online learning

3. Develop and deploy advanced online data pipelines

DATA ENGINEER

Overview

They started with a singular belief - what is beautiful cannot and should not be defined in marketing meetings. It's defined by the regular people like us, our sisters, our next-door neighbours, and the friends we make on the playground and in lecture halls. That's why we stand for people-proving everything we do. From the inception of a product idea to testing the final formulations before launch, our consumers are a part of each and every process. They guide and inspire us by sharing their stories with us. They tell us not only about the product they need and the skincare issues they face but also the tales of their struggles, dreams and triumphs. Skincare goes deeper than skin. It's a form of self-care for many. Wherever someone is on this journey, we want to cheer them on through the products we make, the content we create and the conversations we have. What we wish to build is more than a brand. We want to build a community that grows and glows together - cheering each other on, sharing knowledge, and ensuring people always have access to skincare that really works.

Job Description:

We are seeking a skilled and motivated Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, developing, and maintaining the data infrastructure and systems that enable efficient data collection, storage, processing, and analysis. You will collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to implement data pipelines and ensure the availability, reliability, and scalability of our data platform.

Responsibilities:

Design and implement scalable and robust data pipelines to collect, process, and store data from various sources.

Develop and maintain data warehouse and ETL (Extract, Transform, Load) processes for data integration and transformation.

Optimize and tune the performance of data systems to ensure efficient data processing and analysis.

Collaborate with data scientists and analysts to understand data requirements and implement solutions for data modeling and analysis.

Identify and resolve data quality issues, ensuring data accuracy, consistency, and completeness.

Implement and maintain data governance and security measures to protect sensitive data.

Monitor and troubleshoot data infrastructure, perform root cause analysis, and implement necessary fixes.

Stay up-to-date with emerging technologies and industry trends in data engineering and recommend their adoption when appropriate.

Qualifications:

Bachelor’s or higher degree in Computer Science, Information Systems, or a related field.

Proven experience as a Data Engineer or similar role, working with large-scale data processing and storage systems.

Strong programming skills in languages such as Python, Java, or Scala.

Experience with big data technologies and frameworks like Hadoop, Spark, or Kafka.

Proficiency in SQL and database management systems (e.g., MySQL, PostgreSQL, or Oracle).

Familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery).

Solid understanding of data modeling, data warehousing, and ETL principles.

Knowledge of data integration techniques and tools (e.g., Apache Nifi, Talend, or Informatica).

Strong problem-solving and analytical skills, with the ability to handle complex data challenges.

Excellent communication and collaboration skills to work effectively in a team environment.

Preferred Qualifications:

Advanced knowledge of distributed computing and parallel processing.

Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Apache Flink).

Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).

Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).

Experience with data visualization and reporting tools (e.g., Tableau, Power BI).

Certification in relevant technologies or data engineering disciplines.

Roles and

Responsibilities

Seeking AWS Cloud Engineer /Data Warehouse Developer for our Data CoE team to

help us in configure and develop new AWS environments for our Enterprise Data Lake,

migrate the on-premise traditional workloads to cloud. Must have a sound

understanding of BI best practices, relational structures, dimensional data modelling,

structured query language (SQL) skills, data warehouse and reporting techniques.

 Extensive experience in providing AWS Cloud solutions to various business

use cases.

 Creating star schema data models, performing ETLs and validating results with

business representatives

 Supporting implemented BI solutions by: monitoring and tuning queries and

data loads, addressing user questions concerning data integrity, monitoring

performance and communicating functional and technical issues.

Job Description: -

This position is responsible for the successful delivery of business intelligence

information to the entire organization and is experienced in BI development and

implementations, data architecture and data warehousing.

Requisite Qualification

Essential

-

AWS Certified Database Specialty or -

AWS Certified Data Analytics

Preferred

Any other Data Engineer Certification

Requisite Experience

Essential 4 -7 yrs of experience

Preferred 2+ yrs of experience in ETL & data pipelines

Skills Required

Special Skills Required

 AWS: S3, DMS, Redshift, EC2, VPC, Lambda, Delta Lake, CloudWatch etc.

 Bigdata: Databricks, Spark, Glue and Athena

 Expertise in Lake Formation, Python programming, Spark, Shell scripting

 Minimum Bachelor’s degree with 5+ years of experience in designing, building,

and maintaining AWS data components

 3+ years of experience in data component configuration, related roles and

access setup

 Expertise in Python programming

 Knowledge in all aspects of DevOps (source control, continuous integration,

deployments, etc.)

 Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD

 Hands on ETL development experience, preferably using or SSIS

 SQL Server experience required

 Strong analytical skills to solve and model complex business requirements

 Sound understanding of BI Best Practices/Methodologies, relational structures,

dimensional data modelling, structured query language (SQL) skills, data

warehouse and reporting techniques

Preferred Skills

Required

 Experience working in the SCRUM Environment.

 Experience in Administration (Windows/Unix/Network/Database/Hadoop) is a

plus.

 Experience in SQL Server, SSIS, SSAS, SSRS

 Comfortable with creating data models and visualization using Power BI

 Hands on experience in relational and multi-dimensional data modelling,

including multiple source systems from databases and flat files, and the use of

standard data modelling tools

 Ability to collaborate on a team with infrastructure, BI report development and

business analyst resources, and clearly communicate solutions to both

technical and non-technical team members

• Minimum 3-4 years of experience with ETL tools, SQL, SSAS & SSIS
• Good understanding of Data Governance, including Master Data Management (MDM) and Data Quality tools and processes
• Knowledge of programming languages eg. JASON, Python, R
• Hands on experience of SQL database design
• Experience working with REST API
• Influencing and supporting project delivery through involvement in project/sprint planning and QA
• Working experience with Azure
• Stakeholder management
• Good communication skills

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

Job Overview

We are looking for a Data Engineer to join our data team to solve data-driven critical

business problems. The hire will be responsible for expanding and optimizing the existing

end-to-end architecture including the data pipeline architecture. The Data Engineer will

collaborate with software developers, database architects, data analysts, data scientists and platform team on data initiatives and will ensure optimal data delivery architecture is

consistent throughout ongoing projects. The right candidate should have hands on in

developing a hybrid set of data-pipelines depending on the business requirements.

Responsibilities

• Develop, construct, test and maintain existing and new data-driven architectures.
• Align architecture with business requirements and provide solutions which fits best
• to solve the business problems.
• Build the infrastructure required for optimal extraction, transformation, and loading
• of data from a wide variety of data sources using SQL and Azure ‘big data’
• technologies.
• Data acquisition from multiple sources across the organization.
• Use programming language and tools efficiently to collate the data.
• Identify ways to improve data reliability, efficiency and quality
• Use data to discover tasks that can be automated.
• Deliver updates to stakeholders based on analytics.
• Set up practices on data reporting and continuous monitoring
  
  

Required Technical Skills

• Graduate in Computer Science or in similar quantitative area
• 1+ years of relevant work experience as a Data Engineer or in a similar role.
• Advanced SQL knowledge, Data-Modelling and experience working with relational
• databases, query authoring (SQL) as well as working familiarity with a variety of
• databases.
• Experience in developing and optimizing ETL pipelines, big data pipelines, and datadriven
• architectures.
• Must have strong big-data core knowledge & experience in programming using Spark - Python/Scala
• Experience with orchestrating tool like Airflow or similar
• Experience with Azure Data Factory is good to have
• Build processes supporting data transformation, data structures, metadata,
• dependency and workload management.
• Experience supporting and working with cross-functional teams in a dynamic
• environment.
• Good understanding of Git workflow, Test-case driven development and using CICD
• is good to have
• Good to have some understanding of Delta tables It would be advantage if the candidate also have below mentioned experience using
• the following software/tools:
• Experience with big data tools: Hadoop, Spark, Hive, etc.
• Experience with relational SQL and NoSQL databases
• Experience with cloud data services
• Experience with object-oriented/object function scripting languages: Python, Scala, etc.

• Key responsibility is to design, develop & maintain efficient Data models for the organization maintained to ensure optimal query performance by the consumption layer.
• Developing, Deploying & maintaining a repository of UDXs written in Java / Python.
• Develop optimal Data Model design, analyzing complex distributed data deployments, and making recommendations to optimize performance basis data consumption patterns, performance expectations, the query is executed on the tables/databases, etc.
• Periodic Database health check and maintenance
• Designing collections in a no-SQL Database for efficient performance
• Document & maintain data dictionary from various sources to enable data governance
• Coordination with Business teams, IT, and other stakeholders to provide best-in-class data pipeline solutions, exposing data via APIs, loading in down streams, No-SQL Databases, etc
• Data Governance Process Implementation and ensuring data security

Requirements

• Extensive working experience in Designing & Implementing Data models in OLAP Data Warehousing solutions (Redshift, Synapse, Snowflake, Teradata, Vertica, etc).
• Programming experience using Python / Java.
• Working knowledge in developing & deploying User-defined Functions (UDXs) using Java / Python.
• Strong understanding & extensive working experience in OLAP Data Warehousing (Redshift, Synapse, Snowflake, Teradata, Vertica, etc) architecture and cloud-native Data Lake (S3, ADLS, BigQuery, etc) Architecture.
• Strong knowledge in Design, Development & Performance tuning of 3NF/Flat/Hybrid Data Model.
• Extensive technical experience in SQL including code optimization techniques.
• Strung knowledge of database performance and tuning, troubleshooting, and tuning.
• Knowledge of collection design in any No-SQL DB (DynamoDB, MongoDB, CosmosDB, etc), along with implementation of best practices.
• Ability to understand business functionality, processes, and flows.
• Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently.
• Any OLAP DWH DBA Experience and User Management will be added advantage.
• Knowledge in financial industry-specific Data models such as FSLDM, IBM Financial Data Model, etc will be added advantage.
• Experience in Snowflake will be added advantage.
• Working experience in BFSI/NBFC & data understanding of Loan/Mortgage data will be added advantage.

Functional knowledge

• Data Governance & Quality Assurance
• Modern OLAP Database Architecture & Design
• Linux
• Data structures, algorithm & data modeling techniques
• No-SQL database architecture
• Data Security

What you need to have: