ekSource Technologies Pvt Ltd is an Information Technology Services and solutions company providing IT Consulting and Development Services, such as - Business Process Reengineering and Analysis; System Architecture & Design; Application and Product development and implementation; and Software Integration and Customization services. It is a wholly-owned subsidiary of ekSource Technologies, Inc, a US-based company that has been in business since 2008 with headquarters at Herndon, VA, and development centers in Nashville, TN, and Pune, India. ekSource was founded on a desire to create a business that challenged the traditional values, behaviors, and attitudes of many of the established consultancies and IT service companies.

We pride ourselves on the ability to run projects smoothly and efficiently. We are strong and diverse, committed and steadfast, inventive and resourceful, young, and dynamic.

What we do:

  • ekSource excels in building teams with strong functional knowledge and technical expertise. ekSource partners with leaders in the industry to fully harness their potential and bring the right solutions for our clients and partners Business.
  • Our core capabilities are in Mobile and Web Application Development, Product Engineering and Development, Web API Development and Integration, Predictive BI analytics, Cloud solutioning.
  • We align with our client’s business needs to provide efficient technology-agnostic solutions to their business problems.
  • We leverage Microsoft .NET, Java/J2EE, Android, iOS, Big Data, Sitecore, Pega, and UI/UX technologies to execute IT solutions and product development.
  • We use ‘ekSource Agile’ as our Delivery method with focus towards Continuous and iterative development deliveries and builds with viewable progress to the client.

Roles and Responsibilities

We are hiring for Senior Data Engineer- Machine Learning with solid experience in distributed computing platforms (Hadoop, Apache Spark, Pig, Hive) and Python libraries like SciPy, NumPy, scimitar learn for our projects with different clients executed by ekSource onsite teams.

Role: Senior Data Engineer- Machine Learning

Primary Skills: Data Engineering, Hadoop, Apache Spark, Pig, Hive, Kubernetes, R, Python (SciPy, NumPy, scimitar learn, TensorFlow, Keras, NoSQL/SQL data sources, Databricks, data transformation, data structures, metadata, dependency, workload management

Duration: Full Time- Permanent Role

Job Skills:

  • Solid Data Engineering experience in a Machine Learning environment for more than 10 Years
  • Data modeling and data architecture for structured and unstructured data
  • Experience working with NoSQL/SQL data sources
  • Proficiency using Databricks for data engineering, modeling, and deployment.
  • Experience with distributed computing platforms (Hadoop, Apache Spark, Pig, Hive, etc.)
  • Experience working with Kubernetes
  • Programming experience in Python, R, Java, or Scala
  • Must have experience in CICD tools and software development lifecycle
  • Proficiency with a deep learning framework such as TensorFlow or Keras
  • Experience with Cloud platforms (AWS and GCP preferred)
  • Familiar with software engineering fundamentals and ability to write production-ready code (CI/CD, unit testing, test automation)
  • Experience building REST API endpoints
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Experience building and optimizing big data data pipelines, architectures, and data sets.
  • 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.
  • Ability to architect and implement end-to-end machine learning pipelines, including Docker, Kubernetes, and API development
  • Be a great communicator
  • Bachelor’s Degree with a quantitative focus, ie computer science, math, statistics, economics, or a related discipline, or an additional two years of training/experience in lieu of this degree.
  • Experience working with cross-functional teams (infrastructure engineers, data engineers, data scientists, business analysts, product owners, and software engineers)
  • Experience with version control software and tools (Git, GitHub)
  • Strong project management and organizational skills.

Job Responsibilities:

  • Responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams and responsible for developing necessary API.
  • Document and present findings and recommendations on methodology in a structured way to various stakeholders or partnering teams (Tech, Product leader).
  • Take ownership of whole end-to-end machine learning projects from data processing, training, optimization to real-time monitoring and maintenance
  • Active and effective collaboration with other project team members (other Data Scientist, Data Steward, Machine Learning Engineer)
  • Collaborate to develop analytics pipelines in production systems around continuous integration and learning.
  • Propose suitable technology stacks for projects to be deployed across cloud platforms and on-premises infrastructure.
  • Understand and explain the model and automated decisions to business and technical stakeholders.
  • Critical thinking ability to work in ambiguous situations with unstructured problems
  • Create experiments, algorithms, and prototypes that not only yield high accuracy but are also designed and engineered to scale.
  • Select and employ advanced statistical procedures, ML models, to provide end-users actionable insights.
  • Apply statistics, modeling, and machine learning to improve the efficiency of systems and relevance algorithms across our business application products.
  • Understand business domain, formulate the problem, create and organize data for improving overall machine learning outcome.
  • Understand and explain the model and automated decisions to business and technical stakeholders.
  • Work with data science teams to enable robust decision-making in terms of thinking about scale, latency, throughput requirements.
  • Create tools systems to speedup ML lifecycle Play a significant role in enabling the adoption of sophisticated algorithms and data mining strategies.
  • Domain experience in Storage, Filesystems, hybrid cloud environments is a plus.
  • Support our database architects, data analysts, and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
  • Must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products.

Sonal Chaudhary

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