Deputy Director-ML Engineer, Data Science

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Key Accountabilities:

• Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse.
• Design scalable patterns and architecture to support both batch and real-time data products & platform using big data technologies such as Hadoop, SQL Data Warehouse, EMR, Spark, Data Bricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies.
• Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework.
• Partner with IT, data engineering and other teams on the administration and monitoring of all data platforms to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations.
• Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development.
• Assist with data planning, sourcing, collection, profiling, and transformation.
• Write requirements for ETL and BI developers.
• Test the effectiveness of the database before release for business use.
• Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit.
• Develop repeatable data patterns based on cloud-centric, code-first approaches to data management and cleansing.
• Work with product managers and data stewards within the enterprise data governance process to define and conceptualize data models across enterprise master data, transaction data, and informational data and implement those models into the enterprise data model.
• Partner with the data science team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders.
• Design data lineage and mapping of source system data to canonical data stores for research, analysis and productization.
• Lead the way in creating next-generation talent for Tech, mentoring internal talent and help leadership in recruiting external talent.
• Help with Intake prioritization, decision making of what to pursue across a wide base of users/stakeholders and across products, databases, and services.

Qualifications/Requirements

• 10+ years of overall technology experience that includes at least 6+ years of hands-on software development, data engineering, and systems architecture.
• 4+ Experience with Azure Data Factory, Databricks and Azure Machine learning.
• 4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• 4+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.
• 4+ years in cloud data engineering experience in at least one cloud (Azure, AWS, GCP).
• Experience in forecasting techniques/predictive Analysis.
• Experience in at least one data modelling tool (ER/Studio, Erwin).
• Experience with integration of multi cloud services with on-premises technologies.
• Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
• Experience with at least one MPP database technology such as Redshift, Synapse or Snowflake.
• Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes.
• Experience with version control systems like GitHub and deployment & CI tools.
• Experience with building solutions in the retail or in the supply chain space is a plus.
• Understanding of metadata management, data lineage, and data glossaries is a plus.
• Working knowledge of agile development, including DevOps and DataOps concepts.
• Familiarity with business intelligence tools (such as Power BI).
• BA/BS in Computer Science, Math, Physics, or other technical fields.