Analytical Engineering Manager I
Charlotte, NC, US, 28210
Banco Popular
Popular te ofrece la red más extensa de sucursales y cajeros automáticos en Puerto Rico. Conoce nuestros productos y servicios para individuos y negocios.The Opportunity
As an Analytical Engineer Manager, you'll hold a significant position within the Analytical Engineering & Enablement pillar, dedicating your advanced expertise to the detailed design, development, and implementation of analytical solutions. Your primary focus will be on data preprocessing, feature engineering, and ensuring smooth data movement, which are essential for guiding informed decision-making and deriving actionable insights. You'll delve into advanced statistical analysis and data transformation techniques to address notable business challenges, thereby enhancing our operational efficacy. Your senior position will also involve providing mentorship and leading initiatives to drive the analytical engineering agenda forward.
Your key responsibilities:
You will collaborate with multifaceted teams of specialists spread across various locations to offer a broad spectrum of data and analytics solutions. You will address complicated challenges and propel advancement within the Enterprise Data & Analytics function.
Specifically:
- Conduct both online and offline feature engineering to enhance the performance and accuracy of analytical models.
- Create and maintain comprehensive data-associated documentation to ensure clear understanding and traceability of data processes and models.
- Define and enforce data quality rules, standards, and metrics to ensure the integrity and accuracy of analytical outputs.
- Establish and promote software engineering best practices within the analytics team to ensure the development of high-quality, reliable analytical solutions.
- Implement and adhere to version control and DataOps principles to ensure the reproducibility and scalability of analytical models and processes.
- Conduct rigorous data testing to identify and rectify errors, inconsistencies, and inaccuracies in analytical models and data processes.
- Utilize appropriate encoding techniques to prepare data for analytical processing, ensuring the robustness and effectiveness of analytical models.
- Collaborate closely with various business units, data engineers, and other stakeholders to understand business challenges, gather requirements, and develop analytical solutions aligned with organizational goals.
- Discover and integrate new data sources and methodologies to improve model accuracy and the overall performance of analytical solutions.
- Stay updated with the latest trends and technologies in data science and analytics, incorporating innovative approaches wherever applicable.
- Conduct extensive data examination and preliminary analysis to identify trends, inherent patterns, and insights within datasets.
- Ensure the integrity, reliability, and robustness of analytical techniques and their resultant outputs through rigorous validation processes.
- Support AI visualization & user-empowered analytics initiatives by contributing to the development of data-driven visualizations that simplify complex analyses for diverse business stakeholders.
- Engage in continuous learning and development, absorbing insights and expertise from senior data scientists and analysts.
- Maintain high standards of compliance concerning data governance, security, and privacy protocols
- Engage and support in the design, development, and implementation of analytical models, which include predictive analytics, advanced clustering algorithms, and machine learning techniques to analyze complex datasets and derive insights.
To qualify for the role, you must have:
- Bachelor’s degree in computer science, Information Systems, Engineering, Statistics, Mathematics, or a related field. A master’s degree in a related field is a plus.
- Minimum 15 years of experience in implementing large scale Data & Analytics platform in AWS, Azure, or Google Cloud, on-prem and Hybrid environment.
- Minimum 5 years of experience in leading and managing various functional teams within ED&A such as data integration, data engineering, analytical engineering, BI / data visualization, Data Operations, or a similar role.
- Experience in leading engineering teams and delivering data capabilities in following waterfall, iterative, scaled agile, scrum, and kanban methodologies.
- In-depth knowledge of data integration methodologies such as change data capture, ETL & ELT processes, real-time data processing, micro-services, data lifecycle management, data lake, data warehouse, data vault, data mesh, data marketplace and data science concepts.
- Hands-on experience with On-prem & cloud data platforms such as Snowflake, AWS Redshift, Azure Synapse Analytics, Databricks, AWS Aurora, Oracle Exadata, SQL server, Hadoop, Spark, SAS and R.
- Proficiency in data integration tools and frameworks such as Informatica PC & IICS, IBM DataStage, DBT, Matillion, Microsoft SSIS, Glue, Batch, Azure data factory, data pipeline, Qlik replicate, Oracle GoldenGate, Shareplex, Apache NiFi and Python based frameworks.
- Experience in Implementing tools and services in data security and data governance domains such as data modeling, data classification, data access control, data masking, data quality, metadata management, catalog, auditing, balancing, reconciliation, and data privacy compliance like GDPR & CCPA.
- Excellent data analysis, profiling and statistics skills coupled with proficiency in SQL tools and technologies such as Oracle, SQL Server, MySQL, Pandas, NumPy, Ggplot, Shiny, SciPy, Sci-Kit Learn, and Matplotlib.
- Strong proficiency in Hive, SQL, Spark, Python, R, SAS or other data manipulation and transformation languages.
- Experience in handling data streams, APIs, events, container orchestration products such OpenShift, EKS, ECS.
- Design both online and offline feature stores, providing efficient data access for machine learning models.
- Implementation experience of one or more AI/ML platforms in cloud such as Sagemaker, Dataiku, DataRobot, H2O.ai, Snowpark, ModelOp Center, and Domino Data Lab.
- Experience in handling high volume of data in structure, semi-structured and unstructured formats such as relational, flat files, XML, JSON, Parquet, Avro, Mainframe copybooks, CSV, Fixed with and hierarchy files.
- Experience with DevOps and DataOps products such as Jenkins, Git, GITLab, Maven, Bitbucket, and Jira.
- Experience in Cloud transformation and implemented various strategies such as Rehost, Re-platform, Repurchase, Refactor / Re-architect , Retire , and Retain.
- Experience with log integration and observability products such as Splunk, Datadog, Grafana, AppDynamics, and CloudWatch.
- Hands-on experience in designing and building data pipelines by leveraging AWS services such as S3, S3 Glacier, EC2, ECS, EMR, Sagemaker, IAM, RDS, DynamoDB, Hive,GraphDB, and DocumentDB.
- Strong analytical, problem-solving, and critical thinking skills.
- Ability to communicate complex data concepts effectively to a diverse array of stakeholders, both technical and non-technical.
- Exposure to financial analytics, customer analytics, segmentation, or in-market hypothesis testing is considered advantageous.
- A passion for continuous learning and staying abreast of industry innovations and trends
What we look for:
We are seeking enthusiastic and proactive leaders who have a clear vision and an unwavering commitment to remain at the forefront of data technology and science. Our ideal candidates are those who aim to foster team spirit and collaboration and have a knack for adept management. It is essential that you display comprehensive technical proficiency and possess a rich understanding of the industry.
If you have a genuine drive for helping consumers achieve the full potential of their data while working towards your own development, this role is for you.
Region Locations
North Carolina or Puerto Rico
Important: The candidate must provide evidence of academic preparation or courses related to the job posting, if necessary.
ABOUT US
Popular is Puerto Rico’s leading financial institution and have been evolving since it was founded over a century ago. From a small bank it has developed into a large corporation that offer a wide variety of services and financial solutions to our customers, with presence in the United States, the Caribbean and Latin America.
As employees, we are dedicated to making our customers dreams come true by offering financial solutions in each stage of their life. Our extensive trajectory demonstrates the resiliency and determination of our employees to innovate, reach for the right solutions and strongly support the communities we serve; therefore, we value their diverse skills, experiences and backgrounds.
We reaffirm our commitment to always offer essential financial services and solutions for our customers and communities, including during emergency situations and/or natural disasters. Popular’s employees are considered essential workers, whose role is critical in the continuity of these important services even under such circumstances. By applying to this position, you acknowledge that Popular may require your services during and immediately after any such events.
If you have a disability or need more information about requesting an accommodation, please contact us at asesorialaboral@popular.com. This email inbox is monitored for such types of requests only. All information you provide will be kept confidential and will be used only to the extent required to provide needed exemptions or reasonable accommodations. Any other correspondence will not receive a response.
Are you ready for a rewarding career?
Popular is an Equal Opportunity Employer
Learn more about us at www.popular.com and keep updated with our latest job postings at www.jobs.popular.com.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs Avro AWS Azure Bitbucket Classification Clustering Computer Science CSV Data analysis Databricks Data governance DataOps Data pipelines Data quality DataRobot Data visualization Data warehouse dbt DevOps DynamoDB EC2 ECS ELT Engineering ETL Feature engineering GCP Git GitLab Google Cloud Grafana Hadoop Informatica Jenkins Jira JSON Kanban Machine Learning Mathematics Matillion Matplotlib Maven ML models MySQL NiFi NumPy Oracle Pandas Parquet Pipelines Privacy Python Qlik R Redshift SageMaker SAS Scikit-learn SciPy Scrum Security Snowflake Spark Splunk SQL SSIS Statistics Testing XML
Perks/benefits: Career development Flat hierarchy Team events
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