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Solutions Architect - DatabricksEXL • United States
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Solutions Architect - Databricks

EXL
  • US
    United States
  • US
    United States
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Über

Data Architect / Lead Data Engineer
We are seeking a highly skilled and hands-on Data Architect / Lead Data Engineer to design, build, and scale modern data platforms leveraging the Databricks Lakehouse architecture. This role combines deep technical expertise, architecture design, and client-facing leadership, with an emphasis on driving Databricks adoption across enterprise data ecosystems. Responsibilities
Partner with client stakeholders to define data platform strategy and establish Databricks Lakehouse architecture as the standard. Design scalable, secure, and high-performance data architectures across batch and real-time processing. Build and present reference architectures, solution blueprints, and demos to drive adoption and technical buy-in. Translate complex business requirements into robust technical data solutions. Design and implement scalable data pipelines using Databricks (PySpark, SQL). Build and optimize data models, data marts, and medallion architecture layers (Bronze/Silver/Gold). Develop and manage ETL/ELT pipelines, including CDC, incremental processing, and performance tuning. Ensure data quality, observability, monitoring, and alerting across production workloads. Work with large-scale distributed data systems (Spark, Kafka, etc.). Lead and mentor a team of data engineers across multiple workstreams. Conduct code reviews, enforce best practices, and create reusable frameworks/patterns. Drive end-to-end solution delivery, including architecture, development, and production deployment. Collaborate with cross-functional teams including analytics, BI, data science, and cloud engineering. Manage stakeholder communication and provide technical thought leadership. Expected work split: 50% Hands-on Technical: Data engineering, pipeline development, architecture implementation 50% Leadership & Client Engagement: Solution design, stakeholder management, team leadership Qualifications
6-10 years of experience in data engineering, data architecture, or analytics engineering Strong experience with Databricks ecosystem (Spark, SQL, PySpark, workflows) Expertise in:
Big Data Technologies (Spark, Kafka, distributed systems) Data Warehousing & Modeling (OLTP/OLAP, dimensional modeling, medallion architecture) ETL/ELT pipeline development and orchestration (Airflow or similar tools)
Advanced proficiency in SQL and Python (Scala/Java/R is a plus) Experience designing and delivering enterprise-grade data architectures Strong understanding of performance tuning, query optimization, and large-scale data processing Proven ability to translate business needs into scalable technical solutions Experience leading teams and working in client-facing environments Excellent communication, problem-solving, and stakeholder management skills Required Skills
Data Architecture Data Strategy ETL Design Interpersonal Dynamics with Coworkers Resource Management Results Orientation Time Management Skills Working under Pressure Writing Communication Skills About Us
EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world's leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents.
  • United States

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