Data & Analytics Lead

Primary Job Duties & Responsibilities

• Lead development and production deployment of enterprise-level analytic data products (also potentially pilots and proof of concepts), determining appropriate design strategies and methodologies.
• Find creative solutions to challenging problems involving factors with potentially broad implications; reflecting on solutions, measuring impact, and using that information to ideate and optimize.
• Execute data strategies with an understanding of enterprise architecture, consumption patterns, platforms and application infrastructure.
• Develop business partnerships and influence priorities by identifying solutions that are aligned with current business objectives and closely follow industry trends.
• Communicate with partners, describing technology concepts in ways the business can understand, documenting initiatives in a concise and clear manner, and empathetically and actively listening to other's thoughts and ideas.
• Partner with data management & information security colleagues to ensure the protection of highly sensitive datasets.
• Maintain relationships with partner teams to ensure needs are met and impacted areas plan work accordingly.
• Present analysis and recommendations to help influence strategic decisions.
• Lead and take action, inspire and motivate others, and be effective at influencing team members.
• Guide and coach team members, focusing on individual's professional development as well as overall team health and technical proficiency.

What Will Our Ideal Candidate Have

• Preferably 10+ years of work experience building, managing, and leading high-performing, diverse, collaborative, and geographically distributed data engineering teams.
• Demonstrated ability as a strategic technical partner, working collaboratively with data analytics, data science, product, engineering, and other cross-functional partners, to plan, prioritize, and achieve company goals.
• Experience starting, leading, and evolving technical forums, with effective soft skills, as well as representing data engineering and architectural considerations in cross-team settings.
• Experience developing and nurturing data engineering talent, including implementing training, upskilling, and mentorship plans. Expert-level engineering, architecture, and system design knowledge, with strong computer science fundamentals.
• Experience developing efficient and scalable production software in Python, Java, or other programming languages commonly used in data engineering
• Understanding of event-driven and/or streaming workflows with tools like Kafka and Spark Aptitude with ETL concepts and tools, including experience ingesting, processing, and transforming a variety of data at scale Proficiency with SQL and NoSQL databases, data warehousing concepts, and cloud-based analytics databases.
• Experience with some of the following tools & platforms (or similar): Azure (ADLS, ADF, AKS, Synapse, Purview), Databricks, Python, JavaScript, Kafka, dbt, Terraform, Snowflake, SQL, Jenkins, Github, Airflow, MLFlow Knowledge and experience with the some of the following concepts: Real-time & Batch Data Processing, Workload Orchestration, Cloud, Datalakes, Data Security, Networking, Serverless, Testing / Test Automation (Unit, Integration, Performance, etc.), WebServices, DevOps, Logging, Monitoring, and Alerting, Containerization, Encryption / Decryption, Data Masking, Cost & Performance Optimization.
• Excellent written and oral communication skills, with a demonstrated ability to communicate complex concepts to a wide range of audiences.
• Ability to thrive in a fast-paced, agile, and dynamic environment, while exuding a can-do attitude Ability to handle multiple concurrent projects while working independently and in teams of all sizes with representatives from a diverse set of technical backgrounds.
• Bachelor's or Master's degree in Computer Science or equivalent; team leadership and management training is a plus.

Primary Job Duties & Responsibilities

• Lead development and production deployment of enterprise-level analytic data products (also potentially pilots and proof of concepts), determining appropriate design strategies and methodologies.
• Find creative solutions to challenging problems involving factors with potentially broad implications; reflecting on solutions, measuring impact, and using that information to ideate and optimize.
• Execute data strategies with an understanding of enterprise architecture, consumption patterns, platforms and application infrastructure.
• Develop business partnerships and influence priorities by identifying solutions that are aligned with current business objectives and closely follow industry trends.
• Communicate with partners, describing technology concepts in ways the business can understand, documenting initiatives in a concise and clear manner, and empathetically and actively listening to other's thoughts and ideas.
• Partner with data management & information security colleagues to ensure the protection of highly sensitive datasets.
• Maintain relationships with partner teams to ensure needs are met and impacted areas plan work accordingly.
• Present analysis and recommendations to help influence strategic decisions.
• Lead and take action, inspire and motivate others, and be effective at influencing team members.
• Guide and coach team members, focusing on individual's professional development as well as overall team health and technical proficiency.

What Will Our Ideal Candidate Have

• Preferably 10+ years of work experience building, managing, and leading high-performing, diverse, collaborative, and geographically distributed data engineering teams.
• Demonstrated ability as a strategic technical partner, working collaboratively with data analytics, data science, product, engineering, and other cross-functional partners, to plan, prioritize, and achieve company goals.
• Experience starting, leading, and evolving technical forums, with effective soft skills, as well as representing data engineering and architectural considerations in cross-team settings.
• Experience developing and nurturing data engineering talent, including implementing training, upskilling, and mentorship plans. Expert-level engineering, architecture, and system design knowledge, with strong computer science fundamentals.
• Experience developing efficient and scalable production software in Python, Java, or other programming languages commonly used in data engineering
• Understanding of event-driven and/or streaming workflows with tools like Kafka and Spark Aptitude with ETL concepts and tools, including experience ingesting, processing, and transforming a variety of data at scale Proficiency with SQL and NoSQL databases, data warehousing concepts, and cloud-based analytics databases.
• Experience with some of the following tools & platforms (or similar): Azure (ADLS, ADF, AKS, Synapse, Purview), Databricks, Python, JavaScript, Kafka, dbt, Terraform, Snowflake, SQL, Jenkins, Github, Airflow, MLFlow Knowledge and experience with the some of the following concepts: Real-time & Batch Data Processing, Workload Orchestration, Cloud, Datalakes, Data Security, Networking, Serverless, Testing / Test Automation (Unit, Integration, Performance, etc.), WebServices, DevOps, Logging, Monitoring, and Alerting, Containerization, Encryption / Decryption, Data Masking, Cost & Performance Optimization.
• Excellent written and oral communication skills, with a demonstrated ability to communicate complex concepts to a wide range of audiences.
• Ability to thrive in a fast-paced, agile, and dynamic environment, while exuding a can-do attitude Ability to handle multiple concurrent projects while working independently and in teams of all sizes with representatives from a diverse set of technical backgrounds.
• Bachelor's or Master's degree in Computer Science or equivalent; team leadership and management training is a plus.