Enterprise Data Operations Sr Analyst

Key Skills

Azure, Data Analytics, Data Lake, Data Warehousing, DevOps, Effective communication skills, ETL/ELT technologies, Machine learning techniques, Optimization, PowerBI, PySpark, Python Programming, Scala Programming, SPARK Programming, SQL

Job Description

• Active contributor to code development in projects and services.
• Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products.
• Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality and performance.
• Responsible for implementing 
• best practices around systems integration, security, performance and data management.
• Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.
• Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.
• Develop and optimize procedures to “productionalize” data science models.
• Define and manage SLA’s for data products and processes running in production.
• Support large-scale experimentation done by data scientists.
• Prototype new approaches and build solutions at scale.
• Research in state-of-the-art methodologies.
• Create documentation for learnings and knowledge transfer.
• Create and audit reusable packages or libraries

Qualifications

• 9+ years of overall technology experience that includes at least 3+ years of hands-on software development, data engineering, and systems architecture.
• 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• 3+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.).
• 2+ years in cloud data engineering experience in
• Fluent with Azure cloud services. Azure Certification is a plus.
• Experience with integration of multi cloud services with on-premises technologies.
• Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
• 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 Azure Data Factory, Azure Databricks and Azure Machine learning tools is a plus.
• Experience with Statistical/ML techniques is a plus
• .
• 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 PowerBI).
• BA/BS in Computer Science, Math, Physics, or other technical fields.

Skills, Abilities, Knowledge:

• Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management.
• Proven track record of leading, mentoring data teams.
• Strong change manager. Comfortable with change, especially that which arises through company growth. Able to lead a team effectively through times of change.
• Ability to understand and translate business requirements into data and technical requirements.
• High degree of organization and ability to manage multiple, competing projects and priorities simultaneously.
• Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
• Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs.
• Foster a team culture of accountability, communication, and self-management.
• Proactively drives impact and engagement while bringing others along.
• Consistently attain/exceed individual and team goals
• Ability to lead others without direct authority in a matrixed environment
• Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business.
• Understands both the engineering and business side of the Data Products released. 
• Places the user in the center of decision making. 
• Teams up and collaborates for speed, agility, and innovation. 
• Experience with and embraces agile methodologies. 
• Strong negotiation and decision-making skill. 
• Experience managing and working with globally distributed teams.