Data Warehousing Engineer - Big Data/ETL

Data Scientist-

We are looking for an experienced Data Scientists to join our engineering team and

help us enhance our mobile application with data. In this role, we're looking for

people who are passionate about developing ML/AI in various domains that solves

enterprise problems. We are keen on hiring someone who loves working in fast paced start-up environment and looking to solve some challenging engineering

problems.

As one of the earliest members in engineering, you will have the flexibility to design

the models and architecture from ground up. As any early-stage start-up, we expect

you to be comfortable wearing various hats, and be proactive contributor in building

something truly remarkable.

Responsibilities

Researches, develops and maintains machine learning and statistical models for

business requirements

Work across the spectrum of statistical modelling including supervised,

unsupervised, & deep learning techniques to apply the right level of solution to

the right problem Coordinate with different functional teams to monitor outcomes and refine/

improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation

Identify unexplored data opportunities for the business to unlock and maximize

the potential of digital data within the organization

Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data

Qualifications

3+ years of experience solving complex business problems using machine

learning.

Fluency in programming languages such as Python, NLP and Bert, is a must

Strong analytical and critical thinking skills

Experience in building production quality models using state-of-the-art technologies 

Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is

desirable Ability to collaborate on projects and work independently when required.

Previous experience in Fintech/payments domain is a bonus

You should have Bachelor’s or Master’s degree in Computer Science, Statistics

or Mathematics or another quantitative field from a top tier Institute

ABOUT EPISOURCE:

Episource has devoted more than a decade in building solutions for risk adjustment to measure healthcare outcomes. As one of the leading companies in healthcare, we have helped numerous clients optimize their medical records, data, analytics to enable better documentation of care for patients with chronic diseases.

The backbone of our consistent success has been our obsession with data and technology. At Episource, all of our strategic initiatives start with the question - how can data be “deployed”? Our analytics platforms and datalakes ingest huge quantities of data daily, to help our clients deliver services. We have also built our own machine learning and NLP platform to infuse added productivity and efficiency into our workflow. Combined, these build a foundation of tools and practices used by quantitative staff across the company.

What’s our poison you ask? We work with most of the popular frameworks and technologies like Spark, Airflow, Ansible, Terraform, Docker, ELK. For machine learning and NLP, we are big fans of keras, spacy, scikit-learn, pandas and numpy. AWS and serverless platforms help us stitch these together to stay ahead of the curve.

ABOUT THE ROLE:

We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations, clinical named entity recognition, improving patient health, clinical suspecting and information extraction from clinical notes.

This is a role for highly technical data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.

You will be responsible for setting an agenda to develop and ship data-driven architectures that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company and help build a foundation of tools and practices used by quantitative staff across the company.

During the course of a typical day with our team, expect to work on one or more projects around the following;

1. Create and maintain optimal data pipeline architectures for ML

2. Develop a strong API ecosystem for ML pipelines

3. Building CI/CD pipelines for ML deployments using Github Actions, Travis, Terraform and Ansible

4. Responsible to design and develop distributed, high volume, high-velocity multi-threaded event processing systems

5. Knowledge of software engineering best practices across the development lifecycle, coding standards, code reviews, source management, build processes, testing, and operations  

6. Deploying data pipelines in production using Infrastructure-as-a-Code platforms

7. Designing scalable implementations of the models developed by our Data Science teams  

8. Big data and distributed ML with PySpark on AWS EMR, and more!

BASIC REQUIREMENTS 

1.  Bachelor’s degree or greater in Computer Science, IT or related fields
   
   

2.  Minimum of 5 years of experience in cloud, DevOps, MLOps & data projects
   
   

3. Strong experience with bash scripting, unix environments and building scalable/distributed systems
   
   

4. Experience with automation/configuration management using Ansible, Terraform, or equivalent
   
   

5. Very strong experience with AWS and Python
   
   

6. Experience building CI/CD systems
   
   

7. Experience with containerization technologies like Docker, Kubernetes, ECS, EKS or equivalent

8. Ability to build and manage application and performance monitoring processes

Purpose of Job:

Responsible for drawing insights from many sources of data to answer important business
questions and help the organization make better use of data in their daily activities.

Job Responsibilities:

We are looking for a smart and experienced Data Engineer 1 who can work with a senior
manager to
⮚ Build DevOps solutions and CICD pipelines for code deployment
⮚ Build unit test cases for APIs and Code in Python
⮚ Manage AWS resources including EC2, RDS, Cloud Watch, Amazon Aurora etc.
⮚ Build and deliver high quality data architecture and pipelines to support business
and reporting needs
⮚ Deliver on data architecture projects and implementation of next generation BI
solutions
⮚ Interface with other teams to extract, transform, and load data from a wide variety
of data sources
Qualifications:
Education: MS/MTech/Btech graduates or equivalent with focus on data science and
quantitative fields (CS, Eng, Math, Eco)
Work Experience: Proven 1+ years of experience in data mining (SQL, ETL, data
warehouse, etc.) and using SQL databases

Skills
Technical Skills
⮚ Proficient in Python and SQL. Familiarity with statistics or analytical techniques
⮚ Data Warehousing Experience with Big Data Technologies (Hadoop, Hive,
Hbase, Pig, Spark, etc.)
⮚ Working knowledge of tools and utilities - AWS, DevOps with Git, Selenium,
Postman, Airflow, PySpark
Soft Skills
⮚ Deep Curiosity and Humility
⮚ Excellent storyteller and communicator
⮚ Design Thinking

• 4-7 years of Industry experience in IT or consulting organizations
• 3+ years of experience defining and delivering Informatica Cloud Data Integration & Application Integration enterprise applications in lead developer role
• Must have working knowledge on integrating with Salesforce, Oracle DB, JIRA Cloud  
• Must have working scripting knowledge (windows or Nodejs) 

Soft Skills 

• Superb interpersonal skills, both written and verbal, in order to effectively develop materials that are appropriate for variety of audience in business & technical teams
• Strong presentation skills, successfully present and defend point of view to Business & IT audiences
• Excellent analysis skills and ability to rapidly learn and take advantage of new concepts, business models, and technologies

•  3+ years of experience in Machine Learning
• Bachelors/Masters in Computer Engineering/Science.
• Bachelors/Masters in Engineering/Mathematics/Statistics with sound knowledge of programming and computer concepts.
• 10 and 12th acedemics 70 % & above.

Skills :
 - Strong Python/ programming skills
 - Good conceptual understanding of Machine Learning/Deep Learning/Natural Language            Processing
 - Strong verbal and written communication skills.
 - Should be able to manage team, meet project deadlines and interface with clients.
 - Should be able to work across different domains and quickly ramp up the business                   processes & flows & translate business problems into the data solutions

• Excellent working knowledge on Data Warehousing /Data Migration activity using an ETL tool.
• Strong Data Integration, PostgreSQL/Oracle Database skills, Shell Scripting, Python programming, and development know-how.
• Hands-on experience in working with and generating XML documents.
• Good analytical and business process understanding capability.
• Familiarized with Data Models, Source-Target Data Mapping, Transactional, and Master Data concepts.
• Well-experienced in High level/Detailed design, Performance tuning of ETL jobs.
• Very good communication skills, interpersonal skills, stakeholder management skills, self-motivated, quick learner, team player.
• Exposure to After Sales Business Domain is highly preferred.
• Experience using HP ALM, Jira for ticketing.
• Experience release management

Data Platform engineering at Uber is looking for a strong Technical Lead (Level 5a Engineer) who has built high quality platforms and services that can operate at scale. 5a Engineer at Uber exhibits following qualities: 

• Demonstrate tech expertise › Demonstrate technical skills to go very deep or broad in solving classes of problems or creating broadly leverageable solutions. 
• Execute large scale projects › Define, plan and execute complex and impactful projects. You communicate the vision to peers and stakeholders.
• Collaborate across teams › Domain resource to engineers outside your team and help them leverage the right solutions. Facilitate technical discussions and drive to a consensus.
• Coach engineers › Coach and mentor less experienced engineers and deeply invest in their learning and success. You give and solicit feedback, both positive and negative, to others you work with to help improve the entire team.
• Tech leadership › Lead the effort to define the best practices in your immediate team, and help the broader organization establish better technical or business processes.

What You’ll Do

• Build a scalable, reliable, operable and performant data analytics platform for Uber’s engineers, data scientists, products and operations teams.
• Work alongside the pioneers of big data systems such as Hive, Yarn, Spark, Presto, Kafka, Flink to build out a highly reliable, performant, easy to use software system for Uber’s planet scale of data. 
• Become proficient of multi-tenancy, resource isolation, abuse prevention, self-serve debuggability aspects of a high performant, large scale, service while building these capabilities for Uber's engineers and operation folks.

What You’ll Need

• 7+ years experience in building large scale products, data platforms, distributed systems in a high caliber environment.
• Architecture: Identify and solve major architectural problems by going deep in your field or broad across different teams. Extend, improve, or, when needed, build solutions to address architectural gaps or technical debt.
• Software Engineering/Programming: Create frameworks and abstractions that are reliable and reusable. advanced knowledge of at least one programming language, and are happy to learn more. Our core languages are Java, Python, Go, and Scala.
• Data Engineering: Expertise in one of the big data analytics technologies we currently use such as Apache Hadoop (HDFS and YARN), Apache Hive, Impala, Drill, Spark, Tez, Presto, Calcite, Parquet, Arrow etc. Under the hood experience with similar systems such as Vertica, Apache Impala, Drill, Google Borg, Google BigQuery, Amazon EMR, Amazon RedShift, Docker, Kubernetes, Mesos etc.
• Execution & Results: You tackle large technical projects/problems that are not clearly defined. You anticipate roadblocks and have strategies to de-risk timelines. You orchestrate work that spans multiple teams and keep your stakeholders informed.
• A team player: You believe that you can achieve more on a team that the whole is greater than the sum of its parts. You rely on others’ candid feedback for continuous improvement.
• Business acumen: You understand requirements beyond the written word. Whether you’re working on an API used by other developers, an internal tool consumed by our operation teams, or a feature used by millions of customers, your attention to details leads to a delightful user experience.