Software Engineering Manager - Data
Apple · Software and Services
Apply ↗Skills
["AWS""Azure""GCP""Go""Java""Kafka""Machine Learning""React""SQL""Scala""Snowflake""Spark"]Technology stack
{"programming_languages": ["Java""Go""Scala""SQL"]"frameworks": ["React""Kafka""Spark"]"databases": ["Snowflake"]"cloud": ["AWS""Azure""GCP"]"infrastructure": []"data_tools": []"ai_ml": ["Machine Learning"]"other_tools": []}Description
- Lead and drive Data Warehouse/Business Intelligence development team in building end to end Analytics/AI solutions - Lead the design for data using emerging technologies and tools including Services design and user experience. - Lead the data and analytics solutions using innovative packaged tools and Web technologies based tools (Java and React). - Design and build highly scalable data pipelines using new generation tools and technologies like AWS, Snowflake, Spark, Kafka to induct data from various systems. - Drive the team to develop operationally efficient analytic solutions. - Manage resources/budget and partner with global functional and business teams. Manage multiple teams and projects - Define standards & methodologies for Analytics ecosystem. - Translate complex business requirements into scalable technical solutions meeting data warehousing design standards. Solid understanding of analytics needs and proactive-ness to build generic solutions to improve the efficiency - Lead/Work with cross functional teams ( globally), communicate effectively, both written and verbal with technical and non-technical - Lead and mentor people and plan their career growth and focus on creating a cohesive team environment - Thrives in a dynamic environment, maintaining composure and a positive attitude.
Requirements
["Experience in leading, hiring, developing and building engineering team and providing them technical direction on a day to day basis.", "Experience managing Annual performance reviews, setting SMART goals for team members and invested lead in team member career development.", "Strong Experience working with cloud technologies and big data stack be it Amazon AWS, Snowflake, Microsoft Azure or Google GCP.", "Experience in designing and building dimensional data models to improve accessibility, efficiency and quality of data.", "Bachelor’s Degree or Equivalent with 12+ years of experience in data engineering, computer science or statistics field with at least 4+ years of experience in leadership/management", "Preferred: Experience in building high quality applications, data pipelines and analytics solutions ensuring data privacy and regulatory compliance.", "Preferred: Experience working with Business Stakeholders to understand requirements and ability to translate them into scalable and sustainable solutions.", "Preferred: Should be proficient in writing Advanced SQLs - expertise in performance tuning of SQLs.", "Preferred: Experience with data science and machine learning tools and technologies", "Preferred: Demonstrate good understanding of development processes and agile methodologies", "Preferred: Strong analytical and communication skills.", "Preferred: Should be self-driven, highly motivated and ability to learn quickly and lead by example."]
Roles & responsibilities
["- Lead and drive Data Warehouse/Business Intelligence development team in building end to end Analytics/AI solutions", "- Lead the design for data using emerging technologies and tools including Services design and user experience.", "- Lead the data and analytics solutions using innovative packaged tools and Web technologies based tools (Java and React).", "- Design and build highly scalable data pipelines using new generation tools and technologies like AWS, Snowflake, Spark, Kafka to induct data from various systems.", "- Drive the team to develop operationally efficient analytic solutions.", "- Manage resources/budget and partner with global functional and business teams. Manage multiple teams and projects - Define standards & methodologies for Analytics ecosystem.", "- Translate complex business requirements into scalable technical solutions meeting data warehousing design standards. Solid understanding of analytics needs and proactive-ness to build generic solutions to improve the efficiency", "- Lead/Work with cross functional teams ( globally), communicate effectively, both written and verbal with technical and non-technical", "- Lead and mentor people and plan their career growth and focus on creating a cohesive team environment", "- Thrives in a dynamic environment, maintaining composure and a positive attitude."]
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