User Experience Design
Data Engineer
Data Engineer

Mindstix Labs is looking to hire a passionate Big Data engineer keen on engaging with Fortune 500 companies to setup their Big Data ecosystem. Work experience  on real-world datasets and Big Data tools is a must.

Location: Pune

Experience:1+ years

What you’ll get to do:
Data Science team at Mindstix works on cutting edge technologies. We are looking for a team player who can work independently and take complete ownership of tasks assigned.This person would also take on the following responsibilities:
  • Solve challenging real-world problems using bleeding edge technology and tools.
  • Work with a team of exceptionally talented and dedicated Data Engineers
  • Support business decisions with ad hoc analysis as needed.
  • Selecting and integrating any Big Data tools and frameworks required to provide requested capabilities.
  • Building Scalable Big Data pipeline from scratch for large enterprises.
  • Work closely with other peers to understand various technical options available and hardware, software & financial constraints and then accordingly come up with architecture that will be successful.
  • BYOP - Bring your own process. We like new things
What you should be:
  • The go to person who gets the job done with excellent quality and within stipulated timelines
  • Independent contributor who understands a problem statement and implements analytical solutions & techniques
  • Problem-solver and tinkerer who loves challenges.
  • An impeccable communicator and collaborator who is a thought leader for both customers & colleagues.
  • Team player who thrives on brainstorm sessions.
  • Able to work hand-in-hand with multiple stake holders
  • 1+ experience in building production grade Big Data pipeline from Ground up.
  • Strong knowledge of and experience with statistics; potentially other advanced math as well.
  • Programming experience, ideally in Python/Java/Scala, but we are open to other experience if you’re willing to learn the languages
  • Deep knowledge in Big Data Ecosystem (Cloud preferred)
  • Proficient understanding of distributed computing principles.
  • Management of Hadoop cluster, with all included services.
  • Proficiency with Hadoop v2, MapReduce, HDFS, S3, EMR, Azure Insights
  • Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
  • Experience processing large amounts of structured and unstructured data. MapReduce/Spark experience is a must.
  • Enough programming knowledge to clean and scrub noisy datasets.
  • Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
  • Experience with Apache Spark.
  • Experience with integration of data from multiple data sources
  • Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
  • Knowledge of various ETL techniques and frameworks, such as Flume,NiFi
  • Experience with various messaging systems, such as Kafka or RabbitMQ
  • Experience with Cloudera/MapR/Hortonworks/Azure/AWS Big Data Ecosystems.
  • Fast learner: ability to learn and pick up a new language/tool/ platform quickly.
Good to Have:
  • Experience with Big Data ML toolkits, such as SparkML (Preferred but not mandatory).
  • Cloudera/Hortonworks/AWS/Azure Big Data certification.
Interested?
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4 steps to becoming a Mindstix Ninja
Tell Us About Yourself

Send us your resume, your Github Id, or a blurb about the coolest projects that you've ever created. We love interesting cover letters too! Write to us at careers@mindstix.com.

Preliminary Phone Screening

We chat about your work experience and understand why you really love doing what you do. We also work on programming problems or puzzles during this preliminary screening.

Technical Screening

Most technical interviews are in-person interviews in our labs. Our interview process challenges you to problems in programming logic, data structures, algorithms, and operating systems – the kind of things that make code Ninjas!

Code With Us

Our evaluation process may also need you to write code. We send you a few programming problems, or invite you to our lab to crack-away at code. Plan to spend a day at our lab if you're coming over.