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Principal Solutions Architect - Data Engineering

RemoteIndia only
Published
Role
Data Engineering
Experience
Principal
Employment
Full-time
Salary not disclosed
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No BS summary

Principal Solutions Architect with 15-20 years of experience, including 8+ years as a hands-on Solutions Architect. Requires strong Python/Scala programming, core cloud data platforms (Snowflake, AWS, Azure, Databricks, GCP), dbt, and team leadership experience. Must have client-facing communication skills and a Bachelor's degree in Computer Science or related field.

Core skills

SnowflakeAWSAzure

Required skills

PythonScalaDatabricksGCPSQLdbtSparkKafkaAirflowDelta LakeIcebergHudi

Optional skills

JavaHadoopHDFSS3ADLSGCSKuduElasticsearch

What you'll do

  • Design and implement data solutions.
  • Lead and manage a team comprising Solution Architects and Data Engineers, fostering internal growth through coaching, mentoring, and performance management.
  • Collaborate 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.
  • Resolve challenges and ensure exceptional outcomes for all aspects of project execution.
  • Develop end-to-end technical solutions into production and help ensure performance, security, scalability, and robust data integration.
  • Create and deliver detailed presentations.
  • Create detailed solution documentation (e.g., including POCS and roadmaps, sequence diagrams, class hierarchies, logical system views, etc.).

What they require

  • 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
  • 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.
  • Client-facing written and verbal communication skills and experience
  • 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)

Benefits

  • Remote-First Workplace
  • Medical Insurance for Self & Family
  • Medical Insurance for Parents
  • Term Life & Personal Accident
  • Wellness Allowance
  • Broadband Reimbursement
  • Continuous learning and growth opportunities to enhance your skills and expertise
  • Paid certifications
  • Professional development allowance
  • Bonuses for creating company-approved content

Data and AI Consultancy

NullMid-size
Salary not disclosed