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Lead and administer cloud data warehouse platforms (e.g., Snowflake), design scalable data architectures and models, build and maintain ETL/ELT pipelines, implement CI/CD and version control, optimize performance and costs, migrate/load data from APIs/SaaS/ERP, and ensure security, governance, and testing best practices across the data lifecycle.
Top Skills:
Amazon RedshiftAPIsCi/CdDbtEtl ToolsGitGoogle BigqueryOraclePythonSaas ApplicationsSAPSnowflakeSQLUnix
Financial Services
Lead design and develop scalable, consumer-aligned data products and Delta Lake datasets on Databricks. Build analytics-ready models and PySpark pipelines, ensure data quality, governance, lineage, and performance optimization. Drive AI-assisted engineering practices, collaborate with product, frontend, and analytics teams, and promote reusable data assets for reporting, dashboards, AI, and business applications.
Top Skills:
APIsCi/CdDatabricksDatabricks Lakehouse PlatformDelta LakeOraclePysparkSQL
Big Data • Fitness • Healthtech • Information Technology • Software • Analytics
Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.
Top Skills:
AirflowAmazon RedshiftApache HudiArgo WorkflowsAws AthenaClaudeCptDbtDbt-SparkGitGitGrafanaIcd-10JIRALoincLokiNdcNpiPythonSpark SqlSQL
Must have:
- 7+ years of relevant experience in Data Engineering and delivery.
- 5+ years of relevant work experience in Big Data Concepts. Worked on cloud implementations.
- Strong experience with SQL, python and Pyspark
- Good understanding of Data ingestion and data processing frameworks
- Good experience in Snowflake, SQL, AWS (glue, EMR, S3, Aurora, RDS, AWS architecture)
Good aptitude, strong problem-solving abilities, analytical skills, and ability to take ownership
ResponsibilitiesResponsibilities:
• design, development, and implementation of data solutions using AWS and Snowflake.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Develop and maintain data pipelines, ensuring data quality, integrity, and security.
• Optimize data storage and retrieval processes to support data warehousing and analytics.
• Provide technical leadership and mentorship to junior data engineers.
• Ensure compliance with industry standards and best practices in data engineering.
• Utilize knowledge of insurance, particularly claims and loss, to enhance data solutions
Must have:
- 7+ years of relevant experience in Data Engineering and delivery.
- 5+ years of relevant work experience in Big Data Concepts. Worked on cloud implementations.
- Strong experience with SQL, python and Pyspark
- Good understanding of Data ingestion and data processing frameworks
- Good experience in Snowflake, SQL, AWS (glue, EMR, S3, Aurora, RDS, AWS architecture)
Good aptitude, strong problem-solving abilities, analytical skills, and ability to take ownership
QualificationsRequirements:
- Bachelor’s in engineering or a related field.
- Proven experience as a Data Engineer, with a focus on AWS and Snowflake.
- Strong understanding of data warehousing concepts and best practices.
- Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
- Experience in the insurance industry, preferably with knowledge of claims and loss processes.
- Proficiency in SQL, Python, and other relevant programming languages.
- Strong problem-solving skills and attention to detail.
- Ability to work independently and as part of a team in a fast-paced environment.
- Experience with data modeling and ETL processes.
Familiarity with data governance and data security practices.
The base salary for this position ranges from $130-150k based on skills and experience. Other benefits, including annual bonus may be on top of the base salary.
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. For more information, visit www.exlservice.com.
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