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Greetings!!!!

We are looking for a data engineer for one of our premium clients for their Chennai and Tirunelveli location

Required Education/Experience

● Bachelor’s degree in computer Science or related field

● 5-7 years’ experience in the following:

● Snowflake, Databricks management,

● Python and AWS Lambda

● Scala and/or Java

● Data integration service, SQL and Extract Transform Load (ELT)

● Azure or AWS for development and deployment

● Jira or similar tool during SDLC

● Experience managing codebase using Code repository in Git/GitHub or Bitbucket

● Experience working with a data warehouse.

● Familiarity with structured and semi-structured data formats including JSON, Avro, ORC, Parquet, or XML

● Exposure to working in an agile work environment

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.

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

Ganit has flipped the data science value chain as we do not start with a technique but for us, consumption comes first. With this philosophy, we have successfully scaled from being a small start-up to a 200 resource company with clients in the US, Singapore, Africa, UAE, and India. 

We are looking for experienced data enthusiasts who can make the data talk to them. 

You will: 

• Understand business problems and translate business requirements into technical requirements. 
• Conduct complex data analysis to ensure data quality & reliability i.e., make the data talk by extracting, preparing, and transforming it. 
• Identify, develop and implement statistical techniques and algorithms to address business challenges and add value to the organization. 
• Gather requirements and communicate findings in the form of a meaningful story with the stakeholders  
• Build & implement data models using predictive modelling techniques. Interact with clients and provide support for queries and delivery adoption. 
• Lead and mentor data analysts. 

We are looking for someone who has: 

• Apart from your love for data and ability to code even while sleeping you would need the following. 
• Minimum of 02 years of experience in designing and delivery of data science solutions. 
• You should have successful projects of retail/BFSI/FMCG/Manufacturing/QSR in your kitty to show-off. 
• Deep understanding of various statistical techniques, mathematical models, and algorithms to start the conversation with the data in hand. 
• Ability to choose the right model for the data and translate that into a code using R, Python, VBA, SQL, etc. 
• Bachelors/Masters degree in Engineering/Technology or MBA from Tier-1 B School or MSc. in Statistics or Mathematics 

Skillset Required:

• Regression
• Classification
• Predictive Modelling
• Prescriptive Modelling
• Python
• R
• Descriptive Modelling
• Time Series
• Clustering
•  

What is in it for you: 

• Be a part of building the biggest brand in Data science. 
• An opportunity to be a part of a young and energetic team with a strong pedigree. 
• Work on awesome projects across industries and learn from the best in the industry, while growing at a hyper rate. 

Please Note:  

At Ganit, we are looking for people who love problem solving. You are encouraged to apply even if your experience does not precisely match the job description above. Your passion and skills will stand out and set you apart—especially if your career has taken some extraordinary twists and turns over the years. We welcome diverse perspectives, people who think rigorously and are not afraid to challenge assumptions in a problem. Join us and punch above your weight! 

Ganit is an equal opportunity employer and is committed to providing a work environment that is free from harassment and discrimination. 

All recruitment, selection procedures and decisions will reflect Ganit’s commitment to providing equal opportunity. All potential candidates will be assessed according to their skills, knowledge, qualifications, and capabilities. No regard will be given to factors such as age, gender, marital status, race, religion, physical impairment, or political opinions. 

Skills and requirements

• Experience analyzing complex and varied data in a commercial or academic setting.
• Desire to solve new and complex problems every day.
• Excellent ability to communicate scientific results to both technical and non-technical team members.

Desirable

• A degree in a numerically focused discipline such as, Maths, Physics, Chemistry, Engineering or Biological Sciences..
• Hands on experience on Python, Pyspark, SQL
• Hands on experience on building End to End Data Pipelines.
• Hands on Experience on Azure Data Factory, Azure Data Bricks, Data Lake - added advantage
• Hands on Experience in building data pipelines.
• Experience with Bigdata Tools, Hadoop, Hive, Sqoop, Spark, SparkSQL
• Experience with SQL or NoSQL databases for the purposes of data retrieval and management.
• Experience in data warehousing and business intelligence tools, techniques and technology, as well as experience in diving deep on data analysis or technical issues to come up with effective solutions.
• BS degree in math, statistics, computer science or equivalent technical field.
• Experience in data mining structured and unstructured data (SQL, ETL, data warehouse, Machine Learning etc.) in a business environment with large-scale, complex data sets.
• Proven ability to look at solutions in unconventional ways. Sees opportunities to innovate and can lead the way.
• Willing to learn and work on Data Science, ML, AI.

• 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.

Responsibilities:

• 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

Requirements:

• Experience leading development efforts through all phases of SDLC.
• 5+ 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.
• Team handling preferred for 5+yrs experience candidates.
• Notice period less than 30 days.

• Minimum 1 years of relevant experience, in PySpark (mandatory)
• Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus 
• Ability to play lead role and independently manage 3-5 member of Pyspark development team 
• EMR ,Python and PYspark mandate.
• Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS

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.