Senior Manager Data Engineering - Irvine California, Hybrid, Financial Services

Senior Manager Data Engineering (Irvine California - 3 days in the office).

As a Senior Manager Data Engineering, you will lead and drive the development of scalable, high-performance data solutions leveraging Big Data technologies. You will be responsible for designing, implementing, and optimizing data pipelines, ensuring data quality, and enabling advanced analytics and AI-driven insights. Your expertise in Big Data platforms and cloud-based data architectures will be instrumental in shaping the future of data engineering at scale.

• Lead the design, development, and implementation of large-scale data solutions using Big Data technologies such as Hadoop, Spark, Kafka, and Snowflake.
• Architect and optimize data pipelines, ensuring high performance, scalability, and reliability.
• Collaborate with cross-functional teams to define data engineering best practices and drive data-driven decision-making.
• Implement real-time and batch data processing frameworks to support business intelligence, analytics, and machine learning use cases.
• Ensure data security, governance, and compliance with industry standards and regulations.
• Drive the adoption of cloud-based data platforms (AWS, GCP, Azure) and serverless data architectures.
• Mentor and lead a team of data engineers, fostering a culture of innovation, collaboration, and continuous learning.
• Partner with business stakeholders to understand data requirements and deliver actionable insights.
• Automate data workflows, monitoring, and performance tuning to enhance efficiency.
• Stay ahead of emerging trends in Big Data, AI, and data engineering to drive innovation and competitive advantage.

• 15+ years of experience in data engineering, with a strong focus on Big Data technologies.
• Proven expertise in Hadoop, Spark, Kafka, Flink, and other distributed computing frameworks.
• Hands-on experience with cloud-based data platforms such as AWS and AWS services.
• Strong programming skills in Python, Scala, or Java for data processing and analytics.
• Experience in building and optimizing ETL/ELT pipelines using tools like Apache NiFi, Airflow, or Talend.
• Deep understanding of data modeling, data lakes, and data warehousing concepts.
• Knowledge of SQL, No
  
  SQL databases, and data governance frameworks.
• Strong problem-solving and analytical skills with a focus on performance optimization and scalability.
• Experience in leading and mentoring data engineering teams in an Agile environment.
• Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts into business insights.

• Exceptional data engineering skills with distributed computing background and proven experience in delivering large scale data platforms.
• Good grasp of analytics, measurement, reporting, and business intelligence including modeling, insights generation, and data science.
• Hands-on technologist with deep expertise in big data ecosystem for data integration, data storage, compute framework, analytics, and advanced visualization (e.g., ETL Tools, Streaming Tools, No‑SQL databases, Databricks, Spark, Airflow, ELT tools like DBT, Reporting Tools, AI/ML Platforms).
• Hands-on experience with Amazon Web Services.
• Exposure to AWS EMR, Glue, Athena, S3, SQS/SNS or equivalent technologies in other cloud platforms.
• Experience in building & applying best practices w.r.t. performance, security, and cost‑efficiency for data lake.
• Ability to lead teams that rapidly learn the client’s current digital ecosystem and produce a future data landscape vision and strategy considering the transformation agenda and business goals.
• Have a point of view and understanding of build vs. buy, performance considerations, hosting, commercial models, business intelligence, reporting, and analytics.
• Excellent client communication and facilitating skills, ability to influence others and gain consensus, and team collaboration.
• Combination of proficient consulting, business, strategy, technical and people skills.
• A Bachelor’s degree in Engineering, Computer Science, or related field.

• Certifications in Big Data technologies.
• Experience in real-time data…