
Senior Cloud Data Infrastructure Architect
1 day ago
Imagine a visionary who can design, develop and manage scalable data infrastructure and pipelines while mentoring and inspiring a team of data engineers.
We are seeking an experienced Senior Data Engineering Lead with a strong focus on Databricks and cloud-based data engineering to lead our data engineering team. The leader must have expertise in designing, developing and managing large-scale data pipelines, data lakes and cloud-based data warehouses using Databricks, Apache Spark and Snowflake.
Key Responsibilities:- Lead and manage a team of data engineers providing mentorship technical guidance and fostering a culture of collaboration and innovation.
- Architect design and oversee implementation of large-scale data pipelines data lakes and cloud-based data warehouses using Databricks Apache Spark and Snowflake.
- Develop and optimize ETL/ELT workflows ensuring performance reliability and scalability of data infrastructure.
- Collaborate with business stakeholders data scientists and software teams to understand requirements and translate them into scalable efficient data solutions.
- Implement best practices for data quality governance security and compliance.
- Drive continuous improvement of data engineering processes standards and tools across the organization.
- Support presales activities by contributing to RFPs technical proposals and client engagements.
- Stay abreast of emerging data technologies and trends recommending innovative solutions to enhance analytics capabilities.
- Manage resource planning project prioritization and delivery timelines ensuring alignment with business objectives.
- Lead performance reviews identify skill gaps and champion professional development within the data engineering team.
- Facilitate cross-team communication to streamline data workflows and improve overall delivery.
- Bachelor's or Master's degree in Computer Science Data Science Engineering or a related discipline.
- Minimum 18 years of professional experience in data engineering with at least 12 years in leadership or senior technical roles.
- Deep hands-on expertise with Databricks and Apache Spark for large-scale data processing.
- Strong programming skills in Python Scala or Java.
- Extensive experience with cloud data platforms such as AWS Azure or GCP including services like S3 Redshift BigQuery Snowflake.
- Solid understanding of data modeling data warehousing ETL/ELT design and data lakes.
- Experience with big data technologies like Hadoop Kafka and Databricks ecosystem.
- Knowledge of CI/CD pipelines data orchestration tools e.g. Apache Airflow and data governance best practices.
- Proven experience managing high-performing teams and delivering complex data engineering projects on time.
- Familiarity with analytics solutions and the ability to translate business needs into technical requirements.
- Strong communication skills capable of engaging with both technical teams and senior leadership.
- Experience supporting presales efforts and client technical discussions is a plus.
- Bonus Exposure to machine learning lifecycle and model deployment on Databricks.
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