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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing data solutions using Databricks, Spark, and cloud platforms like AWS, Azure, or GCP. Proven ability to lead architecture sessions, mentor teams, and deliver client-focused presentations while ensuring data governance and quality.
Highest-signal resume keywords
Databricks Solutions ImplementationData Engineering ExpertiseArchitecture Design and DiscoverySQL Query OptimizationTeam Management and Mentoring
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingETLData IntegrationJavaPythonScalaSparkHadoopKafkaSQL
Soft Skills
Strong CommunicationClient-Facing ExperiencePresentation SkillsMentoring
Tools & Technologies
AWSAzureGCPAirflowStreamSetsMatillionFivetranNiFiDbtElasticsearch
Certifications & Qualifications
Associate Developer for Apache SparkData Engineer AssociateProfessional Data EngineerMachine Learning AssociateProfessional ML Engineer
Industry Keywords
Financial ServicesBanking IT ComplianceGovernanceData QualityAnalytics
Tech Stack
Tools & technologiesAirflowApacheAWSAzureCassandraElasticSearchETLGoogle Cloud PlatformHadoopHDFSJavaKafkaMatillionNoSQLPandasPythonScalaScikit-LearnSDLCSparkSQL
About the role
Key responsibilities & impact- Serve as a trusted advisor, guiding customers' data engineering and architecture strategy with a focus on Databricks solutions
- Design, build, and deploy comprehensive data solutions for AI, ML, and business intelligence initiatives
- Provide thought leadership on data trends
- Partner with sales teams to present technical solutions to prospective clients
- Manage multiple customer accounts and report on progress and outcomes
- Architect solutions incorporating governance, security, and data quality best practices
- Evaluate data sources and recommend inclusion strategies to strengthen analytics
- Guide internal teams, mentor project teams, and educate end users on data products and analytic environments
- Analyze systems, diagnose data and system defects, and apply appropriate fixes
- Test data movement, transformation code, and data components for accuracy and reliability
- Split time evenly between hands-on technical execution and presales support
Requirements
What you’ll need- 10+ years as a hands-on Solutions Architect and/or Senior Data Engineer
- Recent experience implementing data solutions on Databricks
- Expertise in Spark, Hadoop, Kafka, Databricks, pandas, and scikit-learn
- Deep understanding of data modeling, ETL, data integration, and modern engineering techniques
- Ability to run complex architecture discovery and solution design sessions and create implementation blueprints
- Proficiency in Java, Python, and/or Scala
- Experience with AWS, Azure, and/or GCP
- Ability to write, debug, and optimize SQL queries
- Strong written and verbal communication and client-facing experience
- Ability to build and deliver detailed presentations to clients and stakeholders
- Experience producing detailed solution documentation, including POCs, roadmaps, sequence diagrams, class hierarchies, and logical system views
- Ability to take technical solutions into production with performance, security, scalability, and robust data integration
- Experience managing, mentoring, and growing a team of engineers
- Bachelor's degree in Computer Science or a related field
- Residing in Pacific Time or on the West Coast strongly preferred
- Preferred: familiarity with distributed storage systems including S3, ADLS, HDFS, GCS, Kudu, Elasticsearch/Solr, Cassandra, or other NoSQL systems
- Preferred: experience with Spark, Kafka, StreamSets, Matillion, Fivetran, NiFi, AWS Data Migration Services, Azure Data Factory, and IICS
- Preferred: comprehensive SDLC experience
- Preferred: automated data transformation and curation using dbt, Spark, Spark Streaming, and automated pipelines
- Preferred: workflow management and orchestration using Airflow, AWS Managed Airflow, Luigi, and NiFi
- Preferred: Financial Services, preferably banking, domain background
- Preferred: understanding of banking IT compliance requirements and standards
- Preferred: at least two listed certifications: Associate Developer for Apache Spark, Data Engineer Associate, Professional Data Engineer, Machine Learning Associate, or Professional ML Engineer
Benefits
Comp & perks- Health insurance coverage for employees and eligible family members from the first day of employment
- Minimum of 20 days paid time off annually
- Nine paid company holidays
- Opportunities for professional development and career advancement
- Opportunity to grow technical and people skills
- Performance-based cash incentive awards
- Innovative environment with cutting-edge technologies and industry leaders
- Collaborative culture emphasizing collaboration and knowledge sharing