Job Description

WHAT WE DO


Transforming how businesses optimize their data operations with our industry-leading Data Observability platform. We help organizations maximize performance, reduce costs, and ensure reliability across complex data ecosystems including Databricks, Snowflake, BigQuery, Amazon EMR, Spark, and Kafka. Our intelligent platform empowers data teams to troubleshoot faster, automate optimization, and extract more value from their data infrastructure investments.


ROLE DESCRIPTION


We are seeking a seasoned Solution Architect with deep expertise in Databricks, Snowflake, and modern cloud data platforms. This high-impact role bridges pre-sales engineering, solution design, and customer success, helping our prospects and customers achieve optimal outcomes with our Data Observability platform. You will partner closely with sales, product, and engineering teams to design scalable architectures, deliver compelling demos, and guide enterprise clients through successful adoption.
ROLES AND RESPONSIBILITIES

Lead technical discovery and architecture workshops with enterprise customers and prospects. Design end-to-end data solutions leveraging Databricks, Snowflake, Spark, and cloud platforms (AWS/GCP/Azure). Build and deliver high-impact demos, proofs-of-concept, and technical presentations for pre-sales engagements. Provide expert guidance on data pipeline optimization, cost management, and performance tuning using our platform. Collaborate with product management to relay market feedback and influence roadmap priorities. Mentor and enable sales engineers and partner teams on best practices for large-scale data architecture. Ensure smooth hand-off from pre-sales to delivery, supporting early implementation success.

SKILLS REQUIRED

8-10 years of experience in data engineering, architecture, or solution consulting with at least 4+ years in pre-sales or customer-facing roles. Deep hands-on expertise with Databricks (Delta Lake, Spark, MLflow) and Snowflake (data warehousing, Snowpark, performance optimization). Strong understanding of big-data and cloud-native architectures, including serverless and microservices patterns. Proven ability to create architecture diagrams, sizing estimates, and implementation plans. Excellent presentation, whiteboarding, and stakeholder-management skills for executive and technical audiences. Familiarity with complementary ecosystems such as Kafka, Airflow, dbt, or similar. Strong problem-solving mindset and a passion for helping customers succeed.
GOOD TO HAVE

Certifications in Databricks, Snowflake, or major cloud platforms (AWS/GCP/Azure). Experience in data observability, monitoring, or performance tuning solutions. * Background in data governance, security, or regulatory compliance frameworks.