Solutions Architect

SunnyData

. Serve as a trusted advisor to customers on data engineering and data architecture needs, focusing on Databricks solutions .

Posted 10/21/2026full-timeRemote • Argentina, Uruguay, MexicoSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing data solutions using Databricks, Spark, and cloud platforms like AWS, Azure, or GCP. Proficient in data engineering best practices, data governance, and delivering client-facing presentations.

Highest-signal resume keywords

Databricks Solutions ImplementationData Engineering Technologies (Spark, Hadoop, Kafka)Cloud Platforms (AWS, Azure, GCP)SQL Query OptimizationData Analytics Workflows (ETL, Data Integration)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DatabricksSparkHadoopKafkaJavaPythonScalaSQLData ModelingETL Processes

Soft Skills

Strong Communication SkillsClient-Facing ExperienceTeam LeadershipMentoringPresentation Skills

Tools & Technologies

AWSAzureGCPAirflowNiFiStreamsetsMatillionFivetranDbtElasticSearch

Certifications & Qualifications

Associate Developer for Apache SparkData Engineer AssociateProfessional Data EngineerMachine Learning AssociateProfessional ML Engineer

Industry Keywords

Data EngineeringData ArchitectureData GovernanceData QualityBusiness IntelligenceMachine LearningData IntegrationData TransformationDistributed Storage SystemsSoftware Development Lifecycle

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCassandraElasticSearchETLGoogle Cloud PlatformHadoopHDFSJavaKafkaMatillionNoSQLPandasPythonScalaScikit-LearnSparkSQL

About the role

Key responsibilities & impact

Serve as a trusted advisor to customers on data engineering and data architecture needs, focusing on Databricks solutions
Split time evenly between billable work and pre-sales activity
Design, build, and deploy data solutions supporting AI, ML, and business intelligence initiatives
Collaborate with sales teams to present technical solutions to prospective clients
Manage multiple customer accounts, ensure timely delivery, track progress, and report outcomes
Architect data solutions using best practices in data governance, security, and quality
Evaluate data sources and recommend data inclusion strategies
Lead internal teams and mentor project teams
Educate end users on data products and analytic environments
Analyze systems, resolve data and system defects, and apply corrections
Test data movement, transformation code, and data components for accuracy and reliability

Requirements

What you’ll need

7+ years as a hands-on Solutions Architect and/or Senior Data Engineer
Recent experience implementing data solutions with a focus on Databricks
Expertise in data engineering technologies such as Spark, Hadoop, and Kafka
Expertise in the Databricks platform
Knowledge of data science and machine learning technologies such as pandas and scikit-learn
In-depth understanding of end-to-end data analytics workflows, including data modeling, ETL processes, and data integration
Ability to lead complex architecture discovery and solution design sessions
Ability to create implementation architecture 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 skills with client-facing experience
Ability to create and deliver detailed presentations
Experience creating solution documentation, including POCs, roadmaps, sequence diagrams, class hierarchies, and logical system views
Experience leading teams and mentoring engineers
Ability to develop end-to-end technical solutions into production with performance, security, scalability, and robust data integration
Bachelor’s Degree in Computer Science or a related Engineering field
Required English level selection: Basic, Intermediate, or Advance
At least 2 of the listed Databricks certifications are preferred: Associate Developer for Apache Spark, Data Engineer Associate, Professional Data Engineer, Machine Learning Associate, or Professional ML Engineer
Preferred familiarity with distributed storage systems such as S3, ADLS, HDFS, GCS, Kudu, ElasticSearch/Solr, Cassandra, or other NoSQL systems
Preferred experience with data integration technologies including Spark, Kafka, Streamsets, Matillion, Fivetran, NiFi, AWS Data Migration Services, Azure DataFactory, and IICS
Preferred comprehensive software development lifecycle experience
Preferred expertise in automated data transformation and curation using dbt, Spark, Spark Streaming, and automated pipelines
Preferred experience with workflow management and orchestration tools such as Airflow, AWS Managed Airflow, Luigi, and NiFi

Benefits

Comp & perks

Opportunities for professional development and career advancement
Work with cutting-edge technologies and industry leaders in data engineering and AI
Supportive collaborative culture and knowledge sharing
Equal opportunity employment