Data Engineer

Company Profile:

 

Easebuzz is a payment solutions (fintech organisation) company which enables online merchants to accept, process and disburse payments through developer friendly APIs. We are focusing on building plug n play products including the payment infrastructure to solve complete business problems. Definitely a wonderful place where all the actions related to payments, lending, subscription, eKYC is happening at the same time.

 

We have been consistently profitable and are constantly developing new innovative products, as a result, we are able to grow 4x over the past year alone. We are well capitalised and have recently closed a fundraise of $4M in March, 2021 from prominent VC firms and angel investors. The company is based out of Pune and has a total strength of 180 employees. Easebuzz’s corporate culture is tied into the vision of building a workplace which breeds open communication and minimal bureaucracy. An equal opportunity employer, we welcome and encourage diversity in the workplace. One thing you can be sure of is that you will be surrounded by colleagues who are committed to helping each other grow.

 

Easebuzz Pvt. Ltd. has its presence in Pune, Bangalore, Gurugram.

 

Salary: As per company standards.

 

Designation: Data Engineering

 

Location: Pune

 

Experience with ETL, Data Modeling, and Data Architecture

Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties
- Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue.

Experience with AWS cloud data lake for development of real-time or near real-time use cases

Experience with messaging systems such as Kafka/Kinesis for real time data ingestion and processing

Build data pipeline frameworks to automate high-volume and real-time data delivery

Create prototypes and proof-of-concepts for iterative development.

Experience with NoSQL databases, such as DynamoDB, MongoDB etc

Create and maintain optimal data pipeline architecture,

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.

Evangelize a very high standard of quality, reliability and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow

Build and enhance data pipeline architecture by designing and implementing data ingestion solutions.

 

Employment Type

Full-time

 

Role : Sr Data Scientist / Tech Lead – Data Science

Number of positions : 8

Responsibilities

• Lead a team of data scientists, machine learning engineers and big data specialists
• Be the main point of contact for the customers
• Lead data mining and collection procedures
• Ensure data quality and integrity
• Interpret and analyze data problems
• Conceive, plan and prioritize data projects
• Build analytic systems and predictive models
• Test performance of data-driven products
• Visualize data and create reports
• Experiment with new models and techniques
• Align data projects with organizational goals

Requirements (please read carefully)

• Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
• Msc-Statistics/ Phd.Statistics
• Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
• Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
• Proven experience as a Data Scientist or similar role, for about 7-8 years
• Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
• Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
• Knowledge of data management and visualization techniques --- more from a Data Science perspective.
• Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
• Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.

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• Gather information from multiple data sources make Approval Decisions mechanically
• Read and interpret credit related information to the borrowers
• Interpret, analyze and assess all forms of complex information
• Embark on risk assessment analysis
• Maintain the credit exposure of the company within certain risk level with set limit in mind
• Build strategies to minimize risk and increase approval rates
• Design Champion and Challenger tests, implement and read test results
• Build Line assignment strategies

Skills required:
- Credit Risk Modeling
- Statistical Data Understanding and interpretation
- Basic Regression and Advanced Machine Learning Models
- Conversant with coding on Python using libraries like Sklearn etc.
- Build and understand decision trees

MSBI Developer- 

We have the following opening in our organization:

Years of Experience: Experience of  4-8 years. 

Location- Mumbai ( Thane)/BKC/Andheri
Notice period: Max 15 days or Immediate 

Educational Qualification: MCA/ME/Msc-IT/BE/B-Tech/BCA/BSC IT in Computer Science/B.Tech

Requirements:

•   3- 8 years of consulting or relevant work experience
• Should be good in SQL Server 2008 R2 and above.
• Should be excellent at SQL, SSRS & SSIS, SSAS,
• Data modeling, Fact & dimension design, work on a data warehouse or dw architecture design.
• Implementing new technology like power BI, power bi modeling.  
• Knowledge of Azure or R-programming is an added advantage.
• Experiences in BI and Visualization Technology (Tableau, Power  BI).
• Advanced T-SQL programming skill
• Can scope out a simple or semi-complex project based on business requirements and achievable benefits
• Evaluate, design, and implement enterprise IT-based business solutions, often working on-site to help customers deploy their solutions.

Position: Data Engineer  
Location: Chennai- Guindy Industrial Estate
Duration: Full time role
Company: Mobile Programming (https://www.mobileprogramming.com/" target="_blank">https://www.mobileprogramming.com/) 
Client Name: Samsung 

We are looking for a Data Engineer to join our growing team of analytics experts. The hire will be
responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing
data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline
builder and data wrangler who enjoy optimizing data systems and building them from the ground up.
The Data Engineer will support our software developers, database architects, data analysts and data
scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout
ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple
teams, systems and products.

Responsibilities for Data Engineer
 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.
 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.

Qualifications for Data Engineer
 Experience building and optimizing big data ETL pipelines, architectures and data sets.
 Advanced working SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as working familiarity with a variety of databases.
 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 3-6 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: Spark, Kafka, HBase, Hive etc.
 Experience with relational SQL and NoSQL databases
 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, Scala, etc.

Skills: Big Data, AWS, Hive, Spark, Python, SQL

REQUIREMENT:

•  Previous experience of working in large scale data engineering
•  4+ years of experience working in data engineering and/or backend technologies with cloud experience (any) is mandatory.
•  Previous experience of architecting and designing backend for large scale data processing.
•  Familiarity and experience of working in different technologies related to data engineering – different database technologies, Hadoop, spark, storm, hive etc.
•  Hands-on and have the ability to contribute a key portion of data engineering backend.
•  Self-inspired and motivated to drive for exceptional results.
•  Familiarity and experience working with different stages of data engineering – data acquisition, data refining, large scale data processing, efficient data storage for business analysis.
•  Familiarity and experience working with different DB technologies and how to scale them.

RESPONSIBILITY:

•  End to end responsibility to come up with data engineering architecture, design, development and then implementation of it.
•  Build data engineering workflow for large scale data processing.
•  Discover opportunities in data acquisition.
•  Bring industry best practices for data engineering workflow.
•  Develop data set processes for data modelling, mining and production.
•  Take additional tech responsibilities for driving an initiative to completion
•  Recommend ways to improve data reliability, efficiency and quality
•  Goes out of their way to reduce complexity.
•  Humble and outgoing - engineering cheerleaders.

BS/Masters in Computer Science with 4+ years of experience. Excellent knowledge in algorithms and data structures and implementing them in Java. Experience in distributed systems architectures, including multithreading & concurrency issues. Experience working in Agile/Scrum environment is desired. Exceptional debugging, testing, and problem-solving skills. Self-starter, with quick learning curve. Strong written and verbal communication skills and an ability and interest to mentor other junior engineers. Working experience within product development teams is a must. Must have demonstrated capabilities to create patentable ideas. Working experience in Natural Language Processing (NLP)/Natural Language Understanding (NLU) based solutions is a plus.

Job Summary DataToBiz is an AI and Data Analytics Services startup. We are a team of young and dynamic professionals looking for an exceptional data scientist to join our team in Chandigarh. We are trying to solve some very exciting business challenges by applying cutting-edge Machine Learning and Deep Learning Technology. Being a consulting and services startup we are looking for quick learners who can work in a cross-functional team of Consultants, SMEs from various domains, UX architects, and Application development experts, to deliver compelling solutions through the application of Data Science and Machine Learning. The desired candidate will have a passion for finding patterns in large datasets, an ability to quickly understand the underlying domain and expertise to apply Machine Learning tools and techniques to create insights from the data. Responsibilities and Duties As a Data Scientist on our team, you will be responsible for solving complex big-data problems for various clients (on-site and off-site) using data mining, statistical analysis, machine learning, deep learning. One of the primary responsibilities will be to understand the business need and translate it into an actionable analytical plan in consultation with the team. Ensure that the analytical plan aligns with the customer’s overall strategic need. Understand and identify appropriate data sources required for solving the business problem at hand. Explore, diagnose and resolve any data discrepancies – including but not limited to any ETL that may be required, missing value and extreme value/outlier treatment using appropriate methods. Execute project plan to meet requirements and timelines. Identify success metrics and monitor them to ensure high-quality output for the client. Deliver production-ready models that can be deployed in the production system. Create relevant output documents, as required – power point deck/ excel files, data frames etc. Overall project management - Creating a project plan and timelines for the project and obtain sign-off. Monitor project progress in conjunction with the project plan – report risks, scope creep etc. in a timely manner. Identify and evangelize new and upcoming analytical trends in the market within the organization. Implementing the applications of these algorithms/methods/techniques in R/Python Required Experience, Skills and Qualifications 3+ years experience working Data Mining and Statistical Modeling for predictive and prescriptive enterprise analytics. 2+ years of working with Python, Machine learning with exposure to one or more ML/DL frameworks like Tensorflow, Caffe, Scikit-Learn, MXNet, CNTK. Exposure to ML techniques and algorithms to work with different data formats including Structured Data, Unstructured Data, and Natural Language. Experience working with data retrieval and manipulation tools for various data sources like: Rest/Soap APIs, Relational (MySQL) and No-SQL Databases (MongoDB), IOT data streams, Cloud-based storage, and HDFS. Strong foundation in Algorithms and Data Science theory. Strong verbal and written communication skills with other developers and business client Knowledge of Telecom and/or FinTech Domain is a plus.

Requirement Specifications: Job Title:: Data Scientist Experience:: 7 to 10 Years Work Location:: Mumbai, Bengaluru, Chennai Job Role:: Permanent Notice Period :: Immediate to 60 days Job description: • Support delivery of one or more data science use cases, leading on data discovery and model building activities Conceptualize and quickly build POC on new product ideas - should be willing to work as an individual contributor • Open to learn, implement newer tools\products • Experiment & identify best methods\techniques, algorithms for analytical problems • Operationalize – Work closely with the engineering, infrastructure, service management and business teams to operationalize use cases Essential Skills • Minimum 2-7 years of hands-on experience with statistical software tools: SQL, R, Python • 3+ years’ experience in business analytics, forecasting or business planning with emphasis on analytical modeling, quantitative reasoning and metrics reporting • Experience working with large data sets in order to extract business insights or build predictive models • Proficiency in one or more statistical tools/languages – Python, Scala, R, SPSS or SAS and related packages like Pandas, SciPy/Scikit-learn, NumPy etc. • Good data intuition / analysis skills; sql, plsql knowledge must • Manage and transform variety of datasets to cleanse, join, aggregate the datasets • Hands-on experience running in running various methods like Regression, Random forest, k-NN, k-Means, boosted trees, SVM, Neural Network, text mining, NLP, statistical modelling, data mining, exploratory data analysis, statistics (hypothesis testing, descriptive statistics) • Deep domain (BFSI, Manufacturing, Auto, Airlines, Supply Chain, Retail & CPG) knowledge • Demonstrated ability to work under time constraints while delivering incremental value. • Education Minimum a Masters in Statistics, or PhD in domains linked to applied statistics, applied physics, Artificial Intelligence, Computer Vision etc. BE/BTECH/BSC Statistics/BSC Maths