11+ Data mapping Jobs in Chennai | Data mapping Job openings in Chennai

• Should have good hands-on experience in Informatica MDM Customer 360, Data Integration(ETL) using PowerCenter, Data Quality.
• Must have strong skills in Data Analysis, Data Mapping for ETL processes, and Data Modeling.
• Experience with the SIF framework including real-time integration
• Should have experience in building C360 Insights using Informatica
• Should have good experience in creating performant design using Mapplets, Mappings, Workflows for Data Quality(cleansing), ETL.
• Should have experience in building different data warehouse architecture like Enterprise,
• Federated, and Multi-Tier architecture.
• Should have experience in configuring Informatica Data Director in reference to the Data
• Governance of users, IT Managers, and Data Stewards.
• Should have good knowledge in developing complex PL/SQL queries.
• Should have working experience on UNIX and shell scripting to run the Informatica workflows and to control the ETL flow.
• Should know about Informatica Server installation and knowledge on the Administration console.
• Working experience with Developer with Administration is added knowledge.
• Working experience in Amazon Web Services (AWS) is an added advantage. Particularly on AWS S3, Data pipeline, Lambda, Kinesis, DynamoDB, and EMR.
• Should be responsible for the creation of automated BI solutions, including requirements, design,development, testing, and deployment

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

5-7 years of experience in Data Engineering with solid experience in design, development and implementation of end-to-end data ingestion and data processing system in AWS platform.

2-3 years of experience in AWS Glue, Lambda, Appflow, EventBridge, Python, PySpark, Lake House, S3, Redshift, Postgres, API Gateway, CloudFormation, Kinesis, Athena, KMS, IAM.

Experience in modern data architecture, Lake House, Enterprise Data Lake, Data Warehouse, API interfaces, solution patterns, standards and optimizing data ingestion.

Experience in build of data pipelines from source systems like SAP Concur, Veeva Vault, Azure Cost, various social media platforms or similar source systems.

Expertise in analyzing source data and designing a robust and scalable data ingestion framework and pipelines adhering to client Enterprise Data Architecture guidelines.

Proficient in design and development of solutions for real-time (or near real time) stream data processing as well as batch processing on the AWS platform.

Work closely with business analysts, data architects, data engineers, and data analysts to ensure that the data ingestion solutions meet the needs of the business.

Troubleshoot and provide support for issues related to data quality and data ingestion solutions. This may involve debugging data pipeline processes, optimizing queries, or troubleshooting application performance issues.

Experience in working in Agile/Scrum methodologies, CI/CD tools and practices, coding standards, code reviews, source management (GITHUB), JIRA, JIRA Xray and Confluence.

Experience or exposure to design and development using Full Stack tools.

Strong analytical and problem-solving skills, excellent communication (written and oral), and interpersonal skills.

Bachelor's or master's degree in computer science or related field.

Job Responsibilities

• Design, build & test ETL processes using Python & SQL for the corporate data warehouse
• Inform, influence, support, and execute our product decisions
• Maintain advertising data integrity by working closely with R&D to organize and store data in a format that provides accurate data and allows the business to quickly identify issues.
• Evaluate and prototype new technologies in the area of data processing
• Think quickly, communicate clearly and work collaboratively with product, data, engineering, QA and operations teams
• High energy level, strong team player and good work ethic
• Data analysis, understanding of business requirements and translation into logical pipelines & processes
• Identification, analysis & resolution of production & development bugs
• Support the release process including completing & reviewing documentation
• Configure data mappings & transformations to orchestrate data integration & validation
• Provide subject matter expertise
• Document solutions, tools & processes
• Create & support test plans with hands-on testing
• Peer reviews of work developed by other data engineers within the team
• Establish good working relationships & communication channels with relevant departments

Skills and Qualifications we look for

• University degree 2.1 or higher (or equivalent) in a relevant subject. Master’s degree in any data subject will be a strong advantage.
• 4 - 6 years experience with data engineering.
• Strong coding ability and software development experience in Python.
• Strong hands-on experience with SQL and Data Processing.
• Google cloud platform (Cloud composer, Dataflow, Cloud function, Bigquery, Cloud storage, dataproc)
• Good working experience in any one of the ETL tools (Airflow would be preferable).
• Should possess strong analytical and problem solving skills.
• Good to have skills - Apache pyspark, CircleCI, Terraform
• Motivated, self-directed, able to work with ambiguity and interested in emerging technologies, agile and collaborative processes.
• Understanding & experience of agile / scrum delivery methodology

AWS Glue Developer 

Work Experience: 6 to 8 Years

Work Location:  Noida, Bangalore, Chennai & Hyderabad

Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops, 

Job Reference ID:BT/F21/IND

Job Description:

Design, build and configure applications to meet business process and application requirements.

Responsibilities:

7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.

Technical Experience:

Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.

➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.

➢ Create data pipeline architecture by designing and implementing data ingestion solutions.

➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.

➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.

➢ Author ETL processes using Python, Pyspark.

➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.

➢ ETL process monitoring using CloudWatch events.

➢ You will be working in collaboration with other teams. Good communication must.

➢ Must have experience in using AWS services API, AWS CLI and SDK

Professional Attributes:

➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.

➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.

➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.

Qualification:

➢ Degree in Computer Science, Computer Engineering or equivalent.

Salary: Commensurate with experience and demonstrated competence

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

Role : Senior Customer Scientist 

Experience : 6-8 Years 

Location : Chennai (Hybrid) 
 
 

Who are we? 
 
 

A young, fast-growing AI and big data company, with an ambitious vision to simplify the world’s choices. Our clients are top-tier enterprises in the banking, e-commerce and travel spaces. They use our core AI-based choice engine http://maya.ai/">maya.ai, to deliver personal digital experiences centered around taste. The http://maya.ai/">maya.ai platform now touches over 125M customers globally. You’ll find Crayon Boxes in Chennai and Singapore. But you’ll find Crayons in every corner of the world. Especially where our client projects are – UAE, India, SE Asia and pretty soon the US. 
 
 

Life in the Crayon Box is a little chaotic, largely dynamic and keeps us on our toes! Crayons are a diverse and passionate bunch. Challenges excite us. Our mission drives us. And good food, caffeine (for the most part) and youthful energy fuel us. Over the last year alone, Crayon has seen a growth rate of 3x, and we believe this is just the start. 
 

 
We’re looking for young and young-at-heart professionals with a relentless drive to help Crayon double its growth. Leaders, doers, innovators, dreamers, implementers and eccentric visionaries, we have a place for you all. 
 

Can you say “Yes, I have!” to the below? 
 
 

1. Experience with exploratory analysis, statistical analysis, and model development 
    

1. Knowledge of advanced analytics techniques, including Predictive Modelling (Logistic regression), segmentation, forecasting, data mining, and optimizations 
    

1. Knowledge of software packages such as SAS, R, Rapidminer for analytical modelling and data management. 
    

1. Strong experience in SQL/ Python/R working efficiently at scale with large data sets 
    

1. Experience in using Business Intelligence tools such as PowerBI, Tableau, Metabase for business applications 
    

Can you say “Yes, I will!” to the below? 
 
 

1. Drive clarity and solve ambiguous, challenging business problems using data-driven approaches. Propose and own data analysis (including modelling, coding, analytics) to drive business insight and facilitate decisions. 
    

1. Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, statistics, and optimisation, and work with engineering to deploy those algorithms and create impact in production. 
    

1. Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative impact and extract trends 
    

1. Coordinate individual teams to fulfil client requirements and manage deliverable 
    

1. Communicate and present complex concepts to business audiences 
    

1. Travel to client locations when necessary  

Crayon is an equal opportunity employer. Employment is based on a person's merit and qualifications and professional competences. Crayon does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, marital status, pregnancy or related.  
 
 

More about Crayon: https://www.crayondata.com/">https://www.crayondata.com/  
 

More about http://maya.ai/">maya.ai: https://maya.ai/">https://maya.ai/  

4 - 8 overall experience.

• 1-2 years’ experience in Azure Data Factory - schedule Jobs in Flows and ADF Pipelines, Performance Tuning, Error logging etc..
• 1+ years of experience with Power BI - designing and developing reports, dashboards, metrics and visualizations in Powe BI.
• (Required) Participate in video conferencing calls - daily stand-up meetings and all day working with team members on cloud migration planning, development, and support.
• Proficiency in relational database concepts & design using star, Azure Datawarehouse, and data vault.
• Requires 2-3 years of experience with SQL scripting (merge, joins, and stored procedures) and best practices.
• Knowledge on deploying and run SSIS packages in Azure.
• Knowledge of Azure Data Bricks.
• Ability to write and execute complex SQL queries and stored procedures.

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• 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, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: Experience with big
  • data tools: Hadoop, Spark, Kafka, etc.
  • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
  • Experience with AWS cloud services: EC2, EMR, RDS, Redshift
  • Experience with stream-processing systems: Storm, Spark-Streaming, etc.
  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.