Senior Associate - Data Engineer

New York Life • New York, NY

15h • Hybrid

About The Position

As part of Technology, you'll have the opportunity to contribute to groundbreaking initiatives that shape New York Life's digital landscape. Leverage cutting-edge technologies like Generative AI to increase productivity, streamline processes, and create seamless experiences for clients, agents, and employees. Your expertise fuels innovation, agility, and growth — driving the company's success.
We are seeking energetic and passionate Senior Data Engineer to design and execute our company’s modern data management strategy. As a key member of Enterprise Data Platform team, you will work with talented engineers, architects, data scientists and end users to reimagine, design and build the next generation of Insurance solutions in the cloud leveraging nascent and modern technologies and platforms including AWS and Azure cloud, APIs, and AI. You will be responsible for the design, development and deployment of optimal data pipelines taking advantage of leading-edge technologies through experimentation and iterative refinement. You will assist other team members in building and executing automation that effectively and repeatably ensures quality, security, integrity and maintainability of our solutions. You will also be responsible for the evaluation of existing data pipeline architecture, evolve and enhance the foundation, participate in product ideation and technology stack evaluation and recommendations

Requirements

• Eight or more years of experience in enterprise-level delivery of Data Engineering solutions.
• Deep understanding of modern data architecture, including experience with data lakes, data warehouses, data marts, relational and dimensional modeling, data quality, and master data management.
• Experience working with Databricks and DBT
• Strong background in Operational Data Stores, Dimensional Modeling, and supporting application data architecture. Experience with Redshift, Snowflake, Databricks SQL, Oracle, Postgres, MySQL, and understanding of best practice architectural concepts for relational data models.
• 8 + Years of design and implementation of ETL/ELT framework for complex warehouses/data marts.
• Proven experience in ETL/ELT tools IDMC, DBT, AWS Glue.
• Proficiency with languages such as Python, PySpark
• Strong knowledge on AWS Cloud technologies.
• Strong, demonstratable hands-on experience with data engineering and data pipelines
• Proficient in cloud architecture and best practices, particularly with AWS Cloud tools such as Amazon RDS, Redshift, AWS DMS, AWS Glue, Amazon S3, AWS Lambda, and more.
• Hands-on development mentality, with a willingness to troubleshoot and solve complex problems.
• Identify, recommend, and implement ELT processes and architecture improvements.
• Assist and verify design of solution and production of all design phase deliverables.
• Bachelor’s or Master's degree in computer science or an Engineering discipline

Nice To Haves

• Certification in data management (structure and unstructured), and/or cloud architecture or engineering a plus
• Certification in delivery methodologies such as Scaled Agile a plus

Responsibilities

• Engages in collaborative relationships across architecture, product management, data and product delivery teams to design, implement solutions based on defined business challenges and outcomes
• Participate on scrum teams working in short sprints and ensure on time delivery with high quality
• Build and maintain Data engineering solutions on cloud platforms using AWS or Azure services.
• Design, develop, and implement scalable data transformations and ETL/ELT processes using Python, PySpark, and or Data Integration tools IDMC, DBT
• Collaborate with Data Architects and Data analysts to understand data requirements and translate them into scalable, high performant data integration and pipeline solutions.
• Develop and maintain data models and schemas to support data integration and analysis
• Monitor and troubleshoot data pipeline performance, identifying and resolving bottlenecks and issues
• Optimize and tune data integration pipelines for performance, reliability, and scalability
• Implement data quality and validation checks to ensure accuracy and integrity of data through testing
• Build the infrastructure required for optimal ETL/ELT of data from a wide variety of data sources using SQL and AWS big data technologies
• Develop and debug code in PySpark/Spark/Python. Strong SQL and query optimization techniques
• Maintaining high degree of knowledge and expertise in cloud-based technologies contributing to go forward best practices, standards and patterns
• Active participant in relevant communities of practice to exchange ideas and knowledge

Benefits

• We provide a full package of benefits for employees – and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs.
• Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level