Lead Assistant Manager - Data Engineer

Company Overview and Culture EXL (NASDAQ: EXLS) is a global analytics and digital solutions company that partners with clients to improve business outcomes and unlock growth. Bringing together deep domain expertise with robust data, powerful analytics, cloud, and AI, we create agile, scalable solutions and execute complex operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on creating value from data for driving faster decision-making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect. Headquartered in New York, our team is over 40,000 strong, with more than 50 offices spanning six continents. For information, visit www.exlservice.com. For the past 20 years, EXL has worked as a strategic partner and won awards in its approach to helping its clients solve business challenges such as digital transformation, improving customer experience, streamlining business operations, taking products to market faster, improving corporate finance, building models to become compliant more quickly with new regulations, turning volumes of data into business opportunities, creating new channels for growth and better adapting to change. The business operates within four business units: Insurance, Health, Analytics, and Emerging businesses. Job Description: Senior Data Engineer The role involves will contributing with the migration of the existing data platform to on prem Hadoop platform. Implementing standards, governance, and automation. As a senior to the team, this requires coordination and communication skills to work with key stakeholders, data scientist, and other team members. Responsibilities: Design and Develop Data Pipelines: Architect and implement scalable and efficient ETL (Extract, Transform, Load) pipelines using PySpark. Optimize data processing workflows to handle large-scale datasets. Machine Learning Model Development: Develop and train machine learning models using appropriate algorithms and frameworks. Collaborate with data scientists to translate models into production-ready code. MLOps Implementation: Establish and maintain automated CI/CD pipelines for machine learning models. Implement version control for data, models, and code using tools like DVC, MLflow, or similar. Monitor and automate the retraining of models as new data becomes available. Data Quality and Governance: Implement data validation, quality checks, and data governance best practices. Ensure data lineage and documentation for reproducibility and compliance. Performance Tuning: Optimize PySpark jobs for performance, including tuning Spark configurations, optimizing shuffles, and managing memory. Profile and debug PySpark applications to identify and resolve performance bottlenecks. Integration with Cloud Platforms: Deploy and manage data pipelines and machine learning models on cloud platforms (e.g., AWS). Utilize cloud-native services for data storage, processing, and orchestration Collaboration and Communication: Work closely with data scientists, software engineers, and DevOps teams to integrate machine learning models into the broader software infrastructure. Collaborate with business stakeholders to understand requirements and ensure the successful deployment of machine learning solutions. Communicate technical concepts and project status to non-technical stakeholders effectively Qualifications: 8+ years of experience in Engineering field Strong experience with Pyspark, Hadoop (on-prem). Experience with MLOps tools like DVC, MLflow, or similar. Experience with Jupyter, Data Robot, or similar tools. Experience with AWS Sagemaker EEO/Minorities/Females/Vets/Disabilities To view our total rewards offered click here — > https://www.exlservice.com/us-careers-and-benefits Base Salary Range Disclaimer: The base salary range represents the low and high end of the EXL base salary range for this position. Actual salaries will vary depending on factors including but not limited to: location and experience. The base salary range listed is just one component of EXL's total compensation package for employees. Other rewards may include bonuses, as well as a Paid Time Off policy, and many region specific benefits. Please also note that the data shared through the job application will be stored and processed by EXL in accordance with the EXL Privacy Policy. Application & Interview Impersonation Warning – Purposely impersonating another individual when applying and / or participating in an interview in order to obtain employment with EXL Service Holdings, Inc. (the “Company”) for yourself or for the other individual is a crime. We have implemented measures to deter and to uncover such unlawful conduct. If the Company identifies such fraudulent conduct, it will result in, as applicable, the application being rejected, an offer (if made) being rescinded, or termination of employment as well as possible legal action against the impersonator(s). EXL may use artificial intelligence to create insights on how your candidate information matches the requirements of the job for which you applied. While AI may be used in the recruiting process, all final decisions in the recruiting and hiring process will be taken by the recruiting and hiring teams after considering a candidate’s full profile. As a candidate, you can choose to opt out of this artificial intelligence screening process. Your decision to opt out will not negatively impact your opportunity for employment with EXL.