Data Engineer

Who is Tech Mahindra?

 

At Tech Mahindra, we not only provide Agile and DevOps methodologies to our customers, we have adopted the same within the company as well. Our nimble processes are not mired in red tape, yet robust, flexible and result-oriented. We are Software Engineers, Technical Architects, Cloud and DevOps specialists. But the most important, we are dreamers, creators and challengers. Each day, we strive to make great come alive. Our lemma: “work smart and play hard”

Our technology partners are Hashicorp, Cloudbees, Chef, Pagerduty, Docker and SAP.

We are always looking for the brightest candidates to come and we offer a work environment with everything you need to be your best. Does Ambition, Success, Fun, Friends & Learning define your idea of a career? Join us and be part of our family!

 

Skills required:

• 5 + Years of experience
• Fluent in Python and packages related to data processing, such as pandas.
• Fluent in object oriented programming with Python.
• Familiar with database technologies/SQL, data warehouses and related concepts.
• Deploying cloud resources that support data engineering and ML Ops pipelines.
• Setting up CICD pipelines for projects in the data engineering and ML Ops space.
• GitHub experience.
• Fluent in working with large data sets and distributed computing architectures (i.e. Apache Spark).
• Experience with various cloud based data technologies including Databricks, Azure Datalake, Azure Data Explorer (ADX)
• Experience with development of APIs in front of various data technologies.

 

Nice to have skill set:

• Fluent in front end development and deployment of Single Page Applications in one or more Javascript frameworks.
• Relational database – Azure SQL & Oracle. No SQL databases  - MongoDB and/or Cosmos DB
• Exam AZ-900: Microsoft Azure Fundamentals certification

 

Responsible for the ETL (Extract-Transform-Load) procedures of current and historical data from multiple internal/external data sources, in particular:

• E: Extract data from multiple data sources through various available data vendors. Most of the data is structured or semi-structured while a small portion is unstructured.
• T: Transform data to reconcile changes in file formats and schemas over time or across multiple data sources for the same type of information. Align data at various temporal resolutions (e.g., aggregation or disaggregation at various levels in time).
• L: Store files in a structured way for future reference and develop a data schema; deposit data to database for convenient querying and analysis.
• Pipeline for current data: maintain automatic pipelines to ingest data continuously.
• Ingestion and curation of historical data is a one-time effort. Once the ingestion pipelines for most of the data are established and stabilized, the support switches to the maintenance mode for the existing ingestion pipelines and additions of new data sources from time to time.
• Data cleaning to provide quick research turn around, together with a data retrieval API, supported in Excel Add-in and Python packages.

 

 

What you can expect from us

At Tech Mahindra, what distinguishes us from other teams is the comfortable environment which engenders trust within teams and with our customers. Trust and openness leads to quality, innovation, commitment to deliverables, efficiency and cost-effectiveness for all our customers.

• Work with some truly remarkable IT engineers, architects, specialists and more.
• We’re growing at a phenomenal pace and we’d like some company.
• Hear your voice, nurture your talent and help you strengthen your foot print!
• Benefits above the law
• Mentorship, and opportunities to grow and learn

If you apply for this opportunity we will get you resume and its contain personal data whose treatment has been authorized by its owner for Digital OnUs, S. de RL de CV (the "Company”). If you are not the owner of this information or have no relation whatsoever with the subjects treated in it, you are requested in the most attentive way not to make copies of it and / or its attached files and delete it immediately, under the risk of being considered as responsible for the unauthorized treatment of personal data in accordance with the Federal Law on Protection of Personal Data