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SunnyData
SunnyData
51 – 200 Darbinieki
KonsultācijasLoģistikaVeselības aprūpe
SunnyData ir datu inženierijas un mākslīgā intelekta konsultāciju uzņēmums, kas specializējas Databricks. Tā Databricks sertificētie inženieri palīdz organizācijām modernizēt datu platformas, migrēt mantotās uzņēmumu datu noliktavas un datu ezerus, kā arī pārvērst mākslīgā intelekta, mašīnmācīšanās un ģeneratīvā mākslīgā intelekta iniciatīvas praktiski izmantojamās sistēmās. Uzņēmums atbalsta arī datu pārvaldību un MLOps, un tam ir nozares zināšanas veselības aprūpē, finanšu pakalpojumos un loģistikā.
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Vakances uzņēmumā

Principal Solutions Architect, Financial Services — Remote in the United States

Lead the design and delivery of Databricks-based data, machine learning, and AI solutions for customers. The role combines hands-on architecture, presales engagement, customer leadership, and technical mentorship.

USAmerikas Savienotās ValstisAttālinātiPilna slodzeVadošais speciālistsNepieciešamā Valoda: angļuRisinājumu inženieris
AirflowApacheAWSAzureCassandraElasticsearchETLGoogle Cloud PlatformHadoopHDFSJavaKafkaMatillionNoSQLPandasPythonScalaScikit-LearnSDLCSparkSQL

Apraksts

  • Advise customers on data engineering and architecture strategy, with an emphasis on Databricks solutions.
  • Design, develop, and deploy data platforms supporting AI, machine learning, and business intelligence.
  • Offer strategic guidance on evolving data technologies and practices.
  • Collaborate with sales teams to communicate technical solutions to prospective customers.
  • Oversee multiple customer accounts and communicate delivery progress and results.
  • Develop architectures that apply strong governance, security, and data quality practices.
  • Assess data sources and recommend which should be incorporated to improve analytics.
  • Support internal teams, mentor project groups, and train users on data products and analytics environments.
  • Investigate system and data issues, determine root causes, and implement suitable remedies.
  • Validate data pipelines, transformation logic, and related components for accuracy and dependability.
  • Allocate an approximately equal share of time to hands-on technical delivery and presales work.

Prasības

  • At least 10 years of hands-on experience as a Solutions Architect and/or Senior Data Engineer.
  • Recent experience delivering data solutions with Databricks.
  • Expert-level knowledge of Spark, Hadoop, Kafka, Databricks, pandas, and scikit-learn.
  • Strong command of data modeling, ETL, data integration, and modern data engineering practices.
  • Able to lead complex architecture discovery and solution design workshops and produce implementation blueprints.
  • Proficiency in Java, Python, and/or Scala.
  • Experience working with AWS, Azure, and/or Google Cloud Platform.
  • Able to write, troubleshoot, and optimize SQL queries.
  • Excellent written and verbal communication skills, including experience working directly with clients.
  • Able to create and present detailed technical presentations for clients and stakeholders.
  • Experience developing comprehensive solution documentation, including proofs of concept, roadmaps, sequence diagrams, class hierarchies, and logical system views.
  • Able to move technical solutions into production with performance, security, scalability, and reliable data integration in mind.
  • Experience leading, mentoring, and developing engineering teams.
  • Bachelor’s degree in Computer Science or a related discipline.
  • Residence in Pacific Time or on the West Coast is strongly preferred.
  • Preferred: familiarity with distributed storage technologies such as 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: broad experience across the software development life cycle.
  • Preferred: experience automating data transformation and curation with dbt, Spark, Spark Streaming, and automated pipelines.
  • Preferred: experience with workflow management and orchestration tools including Airflow, AWS Managed Airflow, Luigi, and NiFi.
  • Preferred: background in Financial Services, ideally banking.
  • Preferred: knowledge of banking IT compliance requirements and standards.
  • Preferred: at least two of the following certifications: Associate Developer for Apache Spark, Data Engineer Associate, Professional Data Engineer, Machine Learning Associate, or Professional ML Engineer.

Priekšrocības

  • Health insurance for employees and eligible family members begins on the first day of employment.
  • At least 20 paid time-off days each year.
  • Nine paid company holidays.
  • Professional development and career growth opportunities.
  • Opportunities to expand both technical and people-management skills.
  • Performance-based cash incentive awards.
  • Work with emerging technologies and leaders across the industry.
  • Collaborative workplace focused on teamwork and sharing knowledge.

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