Specialist Solutions Architect - Data Engineering & Warehousing
New
D
Databricks, Inc.Data & AI
United StatesFull-TimeSenior
Salary$180,000 — $247,500 USD
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonSQLGCPJavaKafkaAzureScala
Requirements
- 5+ years of experience in a technical role with deep expertise in data and software engineering.
- Hands-on experience with streaming technologies (e.g., Spark Streaming, Kafka), batch ingestion, performance tuning, and troubleshooting complex Spark workloads.
- Experience building or supporting data-driven use cases, predictive analytics pipelines, or customer analytics platforms.
- Experience migrating EDW workloads (e.g., legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems.
- Advanced query tuning, governance, and MPP debugging skills.
- Knowledge of data observability and security, including telemetry, log ingestion, and SIEM tools (e.g., Splunk, Elastic, Sentinel).
- Deep understanding of modern lakehouse architectures (Delta Lake, data modeling, BI integration) across AWS, Azure, or GCP.
- Production-level programming experience in SQL and at least one language among Python, Scala, or Java.
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
- Ability to hit role-specific training and technical delivery milestones within the first 6 months.
- Willingness to travel up to 30% as needed.
Responsibilities
- Provide technical leadership to help enterprise customers successfully build, scale, and optimize big data and large-scale data warehousing workloads.
- Architect production-ready pipelines and demonstrate the power of the Databricks Data Intelligence Platform through end-to-end performance testing, load testing, and optimization.
- Build expertise across specialized domains such as data lake architecture, high-velocity streaming, automated ingestion workflows, and data observability.
- Partner with Solutions Architects on complex pre-sales engagements, including custom proofs of concept (POCs), workload sizing estimations, and custom architecture designs.
- Enable adoption by leading workshops, hackathons, and conference presentations, while actively contributing to the broader Databricks community.
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