Director, Data & Analytics

Catalight

1d•$180,000 - $240,000

About The Position

We are looking for a talented Director of Data & Analytics with a passion for architecting and building modern data infrastructure, BI/ML/AI ready data products, and delivering insights rich analytics solutions. As Director of Data & Analytics, you will own the data strategy, architect the right data platform, and serving analytics ready data products to meet and exceed business needs. You will lead the development of data pipelines and data products necessary to allow BI analysts and AI/ML Engineers to develop predictive and prescriptive analytical solutions. You will contribute to the vision for developing our modern data infrastructure on our cloud platform. You will work closely with business stakeholders and lead a team with various skills including data engineers, BI analysts, data scientists, AI engineers, and data governance analysts. You should possess deep technical skills, be comfortable owning our data strategy and data infrastructure, and be excited about building a strong data foundation for the company. As the Director of Data & Analytics, you will direct the work of your technical workforce, grow junior talent to the best of their capacity, and be hands on in the delivery and execution of work.

Requirements

10 years of experience with modern data engineering projects and practices: designing, building, and deploying scalable data pipelines with 5+ years of experience deploying cloud-based data infrastructure solutions.
Strong programming skills in Python, Java, or Scala, and their respective standard data processing libraries.
3 years of experience building data pipelines for AI/ ML models using PySpark or Python.
Experience building data pipelines with modern tools such as Data Bricks, Fivetran, dbt etc.
Strong experience in establishing and maintaining relational databases, SQL, data warehouses, and ELT pipelines
Experience with Spark, Kafka, etc.
Experienced integrating data from core platforms like EHR, CRM, and Claims Processing into a centralized warehouse and data lake.
Extensive knowledge in statistical modeling, machine learning model development and data science.
Software development best practices with strong rigor in high quality code development, automated testing, and other engineering best practices.
Extensive knowledge of ELT and Data Warehousing concepts, strategies, and methodologies.
Experience working with structured and unstructured data.
Experience establishing real-time data pipelines and processing.
Familiarity with Azure services like Azure functions, Azure Data Lake Store, Azure Cosmos, Azure Databricks, Azure Data Factory etc.
Ability to provide solutions that are forward-thinking in data and analytics.
Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently.
BSc in Computer Science, Engineering, Statistics, Informatics, Information Systems or another quantitative field.
Sensitivity to working with an ethnically, linguistically, culturally, and economically diverse population.
A commitment to the values of the organization while demonstrating good judgment, flexibility, patience and discretion when dealing with confidential and sensitive matters.
Proficient in Microsoft Office (Outlook, Word, Excel, etc.), especially Excel and related computer software.
Consistently demonstrate good judgment and decision-making skills while maintaining the highest level of confidentiality.
Work in an exciting, fast paced high energy environment while effectively multitasking and managing day-to-day responsibilities without supervision.
Personable; able to work comfortably with individuals at all levels within the organization.
Excellent verbal and writing communication skills; frequent proofreading and checking documents for accuracy.
Must be highly detail oriented.
Strong interpersonal skills.
Must be able to communicate effectively within the work environment, read and write using the primary language within the workplace.
Visual and auditory ability to work with clients, staff and others in the workplace continuously.
Frequent speaking and listening (25-75%) to clients, staff, and others in the workplace.
Utilize computer and cell phone for effective communication.
Ability to obtain and maintain criminal record clearance through the Department of Justice (DOJ).
The People & Performance Department must analyze DOJ/FBI live scan reports in accordance with applicable Federal, State, and Local laws, as well as fitness for the position.
Ability to obtain and maintain clearance through the Office of Inspector General.
Must attend any required training.

Nice To Haves

Masters degree in Computer Science or Engineering fields preferred.
In-depth knowledge of Data Bricks, including data processing using Apache Spark, Delta Lake, Unity Catalog, and MLflow is a plus. Ability to design and implement scalable data pipelines and analytics solutions on the Data Bricks platform.

Responsibilities

Cloud Platform Proficiency: Strong understanding and hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP). This includes knowledge of cloud services like compute, storage, networking, and databases.
Data Architecture and Modeling: Proficiency in designing and implementing scalable, high-performance data architectures. Strong understanding of data modeling techniques, including relational, dimensional, and NoSQL data models.
Data Warehousing: Experience in building and managing data warehouses using technologies like Amazon Redshift, Google BigQuery, or Snowflake. Knowledge of optimizing data warehouse performance and cost management.
Data Integration and ELT: Expertise in building Extract, Load, Transform (ELT) processes for ingesting and transforming data from various sources into a unified format.
Big Data Technologies: Proficiency in big data technologies such as Hadoop ecosystem (HDFS, Hive, HBase), Apache Kafka, and Apache Flink. Ability to leverage these technologies for large-scale data processing and real-time analytics.
Programming Skills: Strong programming skills in languages such as Python, Scala, or Java. Ability to write efficient, maintainable code for data processing, analytics, and automation tasks.
Data Governance and Security: Prior experience in implementing data governance principles, data privacy regulations (e.g., HIPAA, GDPR, CCPA), and best practices for ensuring data security and compliance.
Machine Learning and AI: Strong knowledge and deep experience in developing Machine Learning applications. Experience in MLOps and model lifecycle management & model governance in regulated industries like banking and healthcare. Experience in deploying LLM models for custom business use cases.
Data Bricks Expertise: In-depth knowledge of Data Bricks, including data processing using Apache Spark, Delta Lake, Unity Catalog, and MLflow is a plus. Ability to design and implement scalable data pipelines and analytics solutions on the Data Bricks platform.
Leadership and Team Management: Effective leadership skills to lead and mentor a team of data engineers, BI analysts, data scientists, data governance analysts, and AI/ML engineers. Ability to set clear goals, provide guidance, and foster collaboration within the team.
Communication and Stakeholder Management: Strong communication skills to interact with cross-functional teams, senior management, and stakeholders. Ability to translate technical concepts into non-technical terms and influence decision-making.
Problem-solving and Critical Thinking: Aptitude for identifying complex data engineering challenges and devising innovative solutions. Ability to think critically and make data-driven decisions to optimize processes and systems.
Continuous Learning and Adaptability: Commitment to staying updated with the latest advancements in data engineering, cloud technologies, and industry trends. Willingness to adapt to evolving technologies and business requirements.
Develop and implement quality controls and departmental standards to ensure quality standards, organizational expectations, and regulatory requirements.
Contribute to the development and education plans on data engineering capabilities, systems, standards, and processes.
Anticipate future demands of initiatives related to people, technology, budget and business within your department and design/implement solutions to meet these needs.
Communicate results and business impacts of insight initiatives to stakeholders within and outside of the company.