Senior Big Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

At Databricks we work on some of the most complex distributed processing and machine learning problems in the world and our customers challenge us with interesting new big data and AI use cases. As a Senior Specialist Solutions Engineer at Databricks, you will shape the future of big data and the machine learning landscape for leading Fortune 500 organisations.

You will be in a customer-facing role that requires deep hands-on production expertise in Apache SparkTM and data engineering, along with a variety of knowledge of the big data ecosystem.

Weekly, you will guide our largest customers, for example implementing pipelines from data engineering through model building and deployment. You will report to the Senior Manager Resident Solutions Architect. As part of joining Databricks, you will have a direct channel to the developers of Apache Spark, Delta Lake, and MLflow, and the opportunity to present at top big data conferences.

The impact you will have:

• Guide strategic customers as they implement transformational big data projects, including end-to-end development and deployment of industry-leading big data and AI applications
• Use your expertise in data engineering best practices to guide customers to do the same, through building proofs of concept and prototypes, architecting solutions and even pair-programming with customer teams
• Build, and validate migration of workloads from 3rd party databases and data platforms to Apache SparkTM
• Promote Apache SparkTM and Databricks, Delta Lake and MLflow across the developer community through meetups and conferences
• Coordinate with Account Executives, Customer Success Engineers and Solution Architects for expanding the use of Databricks platform within strategic enterprise customers weekly

What we look for:

• Deep hands-on expertise in Apache Spark (Scala or Python)
• 5+ years experience in Design and implementation of Big Data technologies (Apache Spark, Hadoop ecosystem, Apache Kafka, NoSQL databases) and familiarity with data architecture patterns (data warehouse, data lake, streaming, Lambda/Kappa architecture)
• 5+ years experience working as either:
• Software Engineer / Data Engineer / Big Data Engineer: query tuning, performance tuning, troubleshooting, and debugging Spark and other big data solutions.
• Familiarity with a full range of data engineering and data science approaches, covering theoretical best practices and the technical applications of these methods
• Experience building and deploying a range of data engineering pipelines into production, including using automation best practices for CI/CD
• Familiarity with databases and analytics technologies in the industry including Data Warehousing / ETL, Relational Databases, or MPP
• Experience with cloud providers such as AWS, Azure or GCP
• Familiarity with AWS/EC2 cloud deployment models (Public vs. VPC)

Benefits

• Private medical insurance
• Accident coverage
• Employee's Provident Fund
• Equity awards
• Paid parental leave
• Gym reimbursement
• Annual personal development fund
• Work headphones reimbursement
• Business travel insurance