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Big Data Architect
2 weeks ago
As a **Big Data Architect** in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the RSA Manager/Lead.
**The impact you will have**:
- You will work on a variety of impactful customer technical projects which may include building reference architectures, how-to's and production grade MVPs
- Consult on architecture and design; bootstrap or implement strategic customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
- Provide an escalated level of support for customer operational issues.
- You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
- Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
**What we look for**:
- Deep hands-on expertise in **Apache Spark** (Scala or Python)
- ** 8+ 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.
- 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 performance tuning, troubleshooting, and debugging SparkTM and other big data solutions
- Comfortable with talking up and down the IT chain of command including directors, managers, architects and developers
- Experience with cloud providers such as **AWS, Azure or GCP**:
- Familiarity with AWS/EC2 cloud deployment models (Public vs. VPC)
**Benefits**
- Equity awards
- Paid parental leave
- Gym reimbursement
- Annual personal development fund
- Work headphones reimbursement
- Business travel accident insurance
**About Databricks**
Databricks is the data and AI company. More than 7,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems.