Databricks Software Engineering Senior Advisor
4 weeks ago
Help us lead our future. Get ready for a job that encourages you to think strategically yet stay connected with your teams. Do you have problem-solving or technical pipeline experience? If so, prepare to innovate, create, and inspire. The Databricks Software Engineering Senior Advisor (Software Engineering Senior Advisor) demonstrates expertise in data engineering technologies with a focus on engineering, innovation, strategic influence, and product mindset. This individual will act as a key contributor to the team to design, build, test, and deliver large-scale software applications, systems, platforms, services, or technologies in the data engineering space. This individual will have the opportunity to work directly with partner IT and business teams, owning and driving major deliverables across all aspects of software delivery.
Responsibilities
- The candidate will be responsible for delivering business needs end to end, from requirements to development into production.
- This individual will deliver data engineering toolchains, platform capabilities, and reusable patterns through a hands-on engineering approach in the Databricks environment.
- The applicant will be responsible for following software engineering best practices with an automation-first approach and continuous learning and improvement mindset.
- The applicant will ensure adherence to enterprise architecture direction and architectural standards.
- The applicant should be able to collaborate in a high-performing team environment and have the ability to influence and be influenced by others.
Qualifications
- High School diploma; Bachelor’s degree preferred.
- More than 5 years of experience in software engineering, building data engineering pipelines, middleware, API development, and automation
- More than 3 years of experience in Databricks within an AWS environment
- Expertise in Agile software development principles and patterns
- Expertise in building streaming, batch and event-driven architectures and data pipelines
- Cloud-based security principles and protocols like OAuth2, JWT, data encryption, hashing data, secret management, etc.
- Expertise in Big data technologies such as Spark, Hadoop, Databricks, Snowflake, EMR, Glue
- Good understanding of Kafka, Kafka Streams, Spark Structured streaming, configuration-driven data transformation, and curation
- Expertise in building cloud-native microservices, containers, Kubernetes, and platform-as-a-service technologies such as OpenShift, CloudFoundry
- Experience in multi-cloud software-as-a-service products such as Databricks, Snowflake
- Experience in Infrastructure-as-Code (IaC) tools such as terraform and AWS cloudformation
- Experience in messaging systems such as Apache ActiveMQ, WebSphere MQ, Apache Artemis, Kafka, AWS SNS
- Experience in API and microservices stacks such as Spring Boot, Quarkus,
- Expertise in Cloud technologies such as AWS Glue, Lambda, S3, Elastic Search, API Gateway, CloudFront
- Experience with one or more of the following programming and scripting languages – Python, Scala, JVM-based languages, or JavaScript, and ability to pick up new languages
- Experience in building CI/CD pipelines using Jenkins, Github Actions
- Strong expertise in source code management and its best practices
- Proficient in self-testing of applications, unit testing and use of mock frameworks, test-driven development (TDD)
- Knowledge of the Behavioral Driven Development (BDD) approach.
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