Lovelytics
Lovelytics
Lovelytics is a data and AI consultancy serving large enterprises with strategy, engineering, governance, migration, analytics, and modernization services. Its work spans generative AI and machine learning, including LLMOps and MLOps, as well as data visualization and cloud transformation. The company supports Fortune 500 organizations across sectors including energy and utilities, retail and consumer goods, travel, manufacturing, healthcare, life sciences, communications, media, entertainment, gaming, and financial services. Lovelytics also works with major technology platforms such as Databricks, AWS, Microsoft Azure, Google Cloud, and Anthropic.

Senior Data Solution Architect (Remote, United States)

Design scalable Databricks lakehouses, data pipelines, and cloud architectures for enterprise consulting clients. Lead technical delivery and guide data engineering solutions at Lovelytics.

Description

  • Develop long-term data strategies that align client objectives with industry standards
  • Design and oversee enterprise-scale lakehouse and warehouse solutions using Databricks and other cloud-native technologies
  • Build architectures that connect on-premises systems with multiple cloud environments
  • Define batch and streaming ingestion, real-time processing, and ELT/ETL architectures
  • Maintain security, privacy, compliance, and data quality across large-scale environments
  • Resolve complex data engineering problems and make decisions that reduce delivery risk
  • Evaluate and introduce relevant technologies and delivery methods
  • Improve solution performance, cost efficiency, scalability, and maintainability
  • Coach engineers, review architectures and code, and support implementation teams
  • Lead technical discovery, develop solution architectures, answer RFPs, and deliver demonstrations and proofs of concept
  • Produce technical blueprints and advise on tools, frameworks, and architectural patterns
  • Collaborate with sales and account teams to scope projects and develop technical proposals

Requirements

  • Bachelor’s or master’s degree in computer science, engineering, or a related discipline
  • At least 8 years of experience spanning data engineering, analytics architecture, governance, and cloud, including large-scale cloud deployments
  • At least 4 years in a client-facing professional services role involving scoping, architecture development, and presales participation
  • Demonstrated experience designing and delivering modern data lakehouses, warehouses, and pipelines on AWS, Azure, or GCP
  • Expertise in Databricks and Spark is required
  • Experience developing proofs of concept, presenting in technical presales settings, and pricing engagements
  • Strong client communication skills, with the ability to influence technical and executive stakeholders
  • Experience using Google Workspace, macOS, Slack, and Atlassian tools

Benefits

  • Recognition as a Best Place to Work
  • Commitment to equal employment opportunity

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