Specialist Solutions Architect - DE/DWH

Req: FEQ127R163 Location: London Recruiter: Dina Hussain Skills: Data Engineering/DWH As a Specialist Solutions Architect (SSA) - Data Engineering, you will guide customers in building big data solutions on Databricks that span a large variety of use cases. You will be in a customer-facing role, working with and supporting Solution Architects, and will require hands-on production experience with Apache Spark™ and expertise in other data technologies. SSEs help customers through the design and successful implementation of essential workloads while aligning their technical roadmap to expand the use of the Databricks Data Intelligence Platform. As a deep go-to-expert reporting to the Senior Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs, and establish yourself in an area of speciality - whether that be streaming, performance tuning, industry expertise, or more. The impact you will have: Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment Architect production-level data pipelines, including end-to-end pipeline load performance testing and optimisation Become a technical expert in an area such as data lake technology, big data streaming, or big data ingestion and workflows Assist Solution Architects with more advanced aspects of the technical sale, including custom proof of concept content, estimating workload sizing, and custom architectures Provide tutorials and training to improve community adoption (including hackathons and conference presentations) Contribute to the Databricks Community What we look for: Extensive experience in a customer-facing technical role. Pre-sales or post-sales experience working with external clients across a variety of industry markets Nice to have: Databricks Certification Travelling approx. 20-30% of the time Data Engineer Skills Experience as a Data Engineer : query tuning, performance tuning, troubleshooting, and debugging Spark or other big data solutions. Extensive experience building big data pipelines Experience in maintaining and extending production data systems to evolve with complex needs Deep Speciality Expertise in at least one of the following areas: Experience scaling big data workloads (such as ETL) that are performant and cost-effective Experience migrating Hadoop workloads to the public cloud - AWS, Azure, or GCP Experience with large-scale data ingestion pipelines and data migrations - including CDC and streaming ingestion pipelines Expert with cloud data lake technologies - such as Delta and Delta Live Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience Production programming experience in SQL and Python, Scala, or Java Professional experience with Big Data technologies (Ex: Spark, Hadoop, Kafka) and architectures Data Warehousing, Database Skills Experience with the design and implementation of a broad range of analytical and transactional data technologies such as Hadoop, Apache Spark™, NoSQL, OLTP, OLAP, and ETL/ELT. Hands-on experience working with MPP data warehouse appliances (Oracle Exadata, Teradata, IBM Netezza) or cloud data warehouses (Amazon Redshift, Azure Synapse, Snowflake) Hands-on experience with RDBMS systems (PostGres, MySQL, SQL Server, Oracle, MariaDB) Experience in SQL language or any SQL dialect (PL/SQL, Transact-SQL or others) Experience with BI tools such as Power BI, Tableau, Qlik, or others Knowledge of development tools and best practices for data engineers, including CI/CD, unit and integration testing, plus automation and orchestration Expertise in data warehousing - such as query tuning, performance tuning, troubleshooting, and debugging MPP data warehouses or other big data solutions. Maintained, extended, o ... (truncated, view full listing at source)