Principal Solutions Architect - Data Engineering

• Snowflake Implementation Partner of the Year — 7 consecutive years, and 2026 Snowflake AI Partner of the Year
• AWS Premier Tier Services Partner — the highest tier of recognition in the AWS Partner Network
• 2025 Fivetran Partner of the Year (4th consecutive year)
• 2025 dbt Labs Partner of the Year (3x winner) with Visionary partner status
• 2026 KNIME Customer Excellence Partner of the Year
• Preferred Partner in the Anthropic Claude Partner Network
• #1 Partner in Snowflake Advanced Certifications
• 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, and more)
• Recognized as an award-winning workplace in the US, India and LATAM

Join phData, a dynamic and innovative leader in the modern data stack. We partner with major cloud data platforms, including Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean, and dbt, to deliver cutting-edge services and solutions. We're committed to helping global enterprises overcome their toughest data challenges. 

phData is a remote-first global company with employees based in the United States, Latin America, and India. We celebrate the cultures of our team members and foster a community of technological curiosity, ownership, and trust. Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow you the autonomy to deliver results.

• 6x Snowflake Partner of the Year (2020, 2021, 2022, 2023, 2024, 2025)
• Fivetran, dbt, Atlation, and AWS Partner of the Year
• #1 Partner in Snowflake Advanced Certifications
• 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, etc)

Recognized as an award-winning workplace in the US, India, and LATAM

• 15-20 years of Experience with 8+ years as a hands-on Solutions Architect designing and implementing data solutions
• Consulting leadership experience working with external customers, with the ability to multitask, prioritize tasks, frequently change focus, and work across a variety of projects. 
• Strong programming expertise in Python and/or Scala; Java experience is a plus 
• Core cloud data platforms, including Snowflake, AWS, Azure, Databricks, or GCP
• SQL and the ability to write, debug, and optimize SQL queries
• Modern data transformation frameworks: dbt (data build tool) for ELT pipeline development, testing, and documentation within cloud data warehouses
• Demonstrated expertise in effectively leading and managing a team comprising Solution Architects and Data Engineers, fostering internal growth through coaching, mentoring, and performance management.
• Proven track record of collaborating with client stakeholders, technology partners, and cross-functional sales and delivery team members across distributed global teams, ensuring seamless, successful project delivery outcomes.
• Create strong cross-practice relationships to drive customer success.
• Exhibits a strong sense of ownership in resolving challenges, committed to ensuring exceptional outcomes for all aspects of project execution.
• Ability to develop end-to-end technical solutions into production — and to help ensure performance, security, scalability, and robust data integration.
• Client-facing written and verbal communication skills and experience
• Create and deliver detailed presentations 
• Detailed solution documentation (e.g., including POCS and roadmaps, sequence diagrams, class hierarchies, logical system views, etc.)
• 4-year Bachelor's degree in Computer Science or a related field, or a Master's in Computer Applications or equivalent.

• Production experience in core data platforms: Snowflake, AWS, Azure, GCP, Databricks, legacy big data platforms such as Hadoop/HDFS
• Cloud and Distributed Data Storage: S3, ADLS, HDFS, GCS, Kudu, ElasticSearch/Solr, Cassandra, or other NoSQL storage systems
• Data integration technologies: Spark, Kafka, Apache Flink, event/streaming, Streamsets, Matillion, Fivetran, NiFi, AWS Data Migration Services, Azure DataFactory, Informatica Intelligent Cloud Services (IICS), Google DataProc, or other data integration technologies
• Multiple data sources: Experience designing multi-source integration patterns across structured, semi-structured, and unstructured data — including APIs, CDC/event streams, relational databases, NoSQL systems, and file-based sources
• Complete software development life cycle experience: including design, documentation, implementation, testing, and deployment
• Automated data transformation and data curation: Spark, Spark streaming, automated pipelines
• Data observability and quality frameworks: Experience with tools such as Great Expectations, Monte Carlo, or Acceldata; ability to embed data quality checks, lineage tracking, schema monitoring, and freshness alerting into pipeline design
• AI/ML Pipeline Readiness: Experience designing data pipelines and feature stores that support ML/AI workloads; familiarity with MLflow, AWS SageMaker, or Azure ML is a plus
• Workflow Management and Orchestration: Airflow, AWS Managed Airflow, Luigi, NiFi
• Open table formats: Apache Iceberg, Delta Lake (Databricks), Apache Hudi
• Methodologies: Agile Project Management, Data Modeling (e.g., Kimball, Data Vault)