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Job Location: Gurgaon/Gurugram, Bangalore/Bengaluru
WHAT YOU WILL DO:
Core Responsibilities
Establish and implement state-of-art data engineering standards, tools, and techniques across the team.
Collaborate with leaders of other data expertise tracks ? Data Science, Machine Learning, Marketing Science, Operations Research and Primary Research to ensure Engineering are bringing the optimal combination of expertise to deliver results for our clients.
Develop reusable tooling for data ingestion, analysis, visualization, and integration of structured and unstructured data from a variety of data sources.
Design and Implement transformations at scale including cleaning, enriching, de-duping, joining and correlated on structured, semi-structured or unstructured data.
Participate in infrastructure engineering for data ecosystem including development, testing, deployment and release.
Collaborate closely with and influence business consulting staff and leaders as part of multi-disciplinary teams to assess opportunities and develop data driven solutions for clients across a variety of sectors.
Provide technical guidance to external clients and internal stakeholders.
Explore new technical innovations in data engineering to improve customer results.
Advise and coach engineering teams on technology stack best practices and operational models to raise their data engineering capabilities.
Influence, educate and directly support the data engineering capabilities of our clients, often at the executive level.
Travel is required (20%)
Requirements
Bachelors in Computer Science, Engineering, Data Science or a related technical field.
A practitioner of Agile project management techniques such as Scrum and Kanban, and ability to apply these techniques to project work.
7+ years of experience working with a startup or providing services to enterprise customers (Fortune 500, Global 1000)
Four years of experience with data engineering technologies such as Databricks, Snowflake, Kafka, Spark, Airflow or Beam.
Over four years of practical experience programming with Python, R, Scala, Java, C++ or similar data-orientated programming language.
Preferred Qualifications
Master?s degree in Computer Science, Engineering, Data Science or r a related technical field.
Experience with cloud native data engineering services such as AWS EMR, Glue, Kinesis, GCP Dataproc, PubSub, BigQuery, Azure ADF or Synapse Analytics.
Experience with Continuous Integration and Deployment pipelines, ?Infrastructure as Code? technology and containerization. For example, practical experience of Git workflows, Github Actions and Terraform.
Knowledgeable on distributed systems and database internals (including handling consensus, availability, scalability and distributed query processing.
Scaling and optimizing schema and performance tuning data pipelines including orchestration frameworks.
Experience with administering and managing and designing clusters. For example, practical experience of Kubernetes and Helm.
Experience of a modern data science & engineering ecosystem including developing Jupyter notebooks, Numpy, Torch and Tensorflow.
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