Lead Data Architect - Artificial Intelligence/Machine Learning (10-14 yrs)

About the job :

We are looking for a highly skilled Data Architect to be a part, lead and grow our data engineering team, driving the design, development, and maintenance of scalable data pipelines and architecture.

In this role, you will work closely with cross-functional teams, including data science, analytics, software engineering, and business stakeholders, to ensure the delivery of high-quality data solutions that support business objectives.

If you're passionate about data, cloud technologies, and leading high-performing teams, we'd love to hear from you!

Key Responsibilities :

- Design and maintain the overall data architecture strategy to align with business goals

- Own the product/component technical direction and strategy

- Drive tech initiatives and adoption of new technologies, working with the management team to allocate time and resources to the roadmap

- Lead the definition of component standards (code, design, consistency, language, framework) and validate them with engineering teams

- Collaborate with engineering teams on component governance and engineering excellence

- Review code and provide feedback, with the assistance of engineering teams

- Mentor engineers from a technical perspective and communicate the vision and technical status of components

- Understand use cases and design or approve feature technical changes, including building new components

- Keep feature requirements as simple as possible, balancing projected revenue and product needs

- Ensure seamless integration of data across systems and platforms.

- Implement robust data governance frameworks and security measures

- Collaborate closely with cross-functional teams to translate data needs into technical requirements

- Continuously evaluate and integrate emerging technologies and methodologies

- Oversee and manage resource allocation, ensuring optimal utilization

- Manage engineering projects to ensure on-time, within-budget, and quality delivery

Requirements :

- Experience : Minimum of 10+ years of experience in data engineering, with at least 2-3 years in a Architect role.

Technical Expertise :

- Proven experience as a Data Architect with additional expertise in AI/ML, data engineering, and data analysis

- Strong understanding of database systems (e., SQL, NoSQL) and data modeling techniques

- Proficiency in programming languages such as Python, R, or Scala

- Experience with big data technologies (e., Hadoop, Spark, Kafka)

- Knowledge of cloud platforms (e., AWS, Azure, GCP) and their data services

- Familiarity with AI/ML frameworks and libraries (e., TensorFlow, PyTorch, scikit-learn)

- Expertise in data visualization tools (e., Tableau, Power BI)

- Databases: SQL (e., PostgreSQL, MySQL), NoSQL (e., MongoDB, Cassandra)

- Big Data : Hadoop, Spark, Hive, HBase

- Data Warehousing : Snowflake, Amazon Redshift, Google BigQuery

- ETL/ELT Tools : Apache NiFi, Airflow, dbt, Luigi

- Stream Processing : Apache Kafka, Apache Flink

- AI/ML : TensorFlow, PyTorch, scikit-learn, Keras

- Cloud Platforms : AWS (e., S3, EMR, SageMaker), Azure (e., Synapse Analytics, Databricks), GCP (e., BigQuery, Dataflow)

- Data Visualization : Tableau, Power BI, D3.js

- Version Control: Git

- Containerization: Docker, Kubernetes

Preferred :

- Leadership : Proven experience leading and mentoring data engineering teams, fostering a culture of continuous learning and collaboration.

- Excellent communication skills to interpret technical concepts for non-technical stakeholders

- Data Architecture : Expertise in designing scalable and eHicient data architectures, pipelines, and work- ows.

- Problem Solving : Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.

- Communication : Excellent communication skills, capable of collaborating with both technical and non-technical stakeholders.

- Project Management : Experience managing multiple projects and deadlines in a fast-paced environment.

- Bachelor's degree in Computer Science, Data Science, or related field (Master's degree preferred)