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Databricks

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Specialist Solutions Architect - Data Engineering & Warehousing (Digital Native Business)

🗓️ Posted 2026-09-02 United States Hybrid ICT

Company shared salary

Market rate

₹14,000–₹22,000/mo (₹168,000–₹264,000/yr)

Based on similar roles (title + domain + location).

Responsibilities

● Own the end-to-end technical strategy for your accounts, from discovery through production deployment and consumption growth
● Lead complex architecture discussions - designing scalable, production-grade solutions spanning data engineering and real-time analytics
● Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
● Drive technical wins in competitive scenarios by demonstrating Databricks' differentiation through custom-built solutions
● Develop and declare an emerging technical specialization (archetype) - becoming a go-to resource for your team in that domain
● Orchestrate cross-functional resources (DSAs, SAs, Partners) to deliver comprehensive solutions for complex customer needs
● Influence product direction by providing structured feedback on customer requirements and competitive gaps

Requirements

● 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role in the following areas:
● Deep hands-on experience with Apache Spark ecosystem (Spark Core, Spark SQL, Spark Streaming), message queues (e.g., 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
● Strong coding proficiency in Python and SQL - you must demonstrate live coding, debugging, and solution-building skills
● Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
● Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
● Proven ability to lead architecture discussions with senior technical stakeholders - whiteboarding, design reviews, and trade-off analysis
● Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructur
● Nice to have Data Observability & Security: Telemetry, high-velocity log ingestion, anomaly detection, and familiarity with SIEM tools (e.g., Splunk, Elastic, Sentinel)