Technical Data Lead

Job Summary

We are seeking a highly skilled and experienced Technical Data Lead to join our innovative and dynamic team. This role is a unique blend of a Data Engineer, Data Analyst, and Data Scientist, requiring a deep understanding of the entire data lifecycle. The ideal candidate will be a hands-on leader, responsible for guiding a team of data professionals while also being a key individual contributor on complex data initiatives. You will be instrumental in shaping our data strategy, building and maintaining our data infrastructure, and uncovering insights that drive business decisions. This role requires a strong foundation in MLOps, DevOps, and AIOps to ensure our data solutions are scalable, reliable, and efficient.

Responsibilities

Data Engineering:

• Design, build, and maintain scalable and reliable data pipelines and ETL/ELT processes.
• Develop and manage data warehousing solutions (e.g., BigQuery, Redshift, Snowflake).
• Ensure data quality, integrity, and governance across all data systems.
• Work with structured and unstructured data from various sources, including APIs, databases, and streaming platforms.
• Implement and manage big data technologies such as Hadoop and Spark.

Data Analysis & Visualization:

• Perform exploratory data analysis to identify trends, patterns, and anomalies in large datasets.
• Develop and maintain dashboards and reports to communicate key business metrics and insights to stakeholders.
• Translate complex data findings into clear and actionable recommendations for both technical and non-technical audiences.
• Utilize BI tools (e.g., Tableau, Power BI) to create compelling data visualizations.

Data Science & Machine Learning:

• Develop and deploy a wide range of machine learning models, including descriptive, predictive, and deep learning models.
• Lead the end-to-end lifecycle of machine learning projects, from problem formulation and data collection to model deployment and monitoring.
• Apply advanced statistical and machine learning techniques to solve complex business problems.
• Stay current with the latest advancements in machine learning and artificial intelligence.

Leadership & Strategy:

• Lead, mentor, and manage a team of data engineers, analysts, and scientists.
• Develop and execute a comprehensive data strategy that aligns with the company's goals and objectives.
• Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to identify and prioritize data-driven opportunities.
• Foster a culture of data-driven decision-making throughout the organization.

MLOps, DevOps, & AIOps:/

• Implement and manage MLOps practices to streamline the deployment, monitoring, and management of machine learning models.
• Utilize DevOps principles and tools to automate and improve our data infrastructure and workflows.
• Leverage AIOps to enhance IT operations through the use of AI and machine learning, improving monitoring, automation, and performance.
• Ensure the reliability, scalability, and efficiency of our data and AI systems.

Qualifications

• Experience:

  8+ years of experience in the data field, with a proven track record of success in data engineering, data analysis, and data science.

• Education:

  Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field.

• Technical Skills:

• Expert proficiency in SQL and at least one programming language such as Python or R.
• Extensive experience with cloud platforms (e.g., AWS, GCP, Azure).
• Hands-on experience with big data technologies (e.g., Spark, Hadoop).
• Strong understanding of database technologies, including both relational (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases.

• Machine Learning Expertise:

• Demonstrated experience in developing and deploying descriptive, predictive, and deep learning models.
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn.

• Leadership:

• Proven experience leading and managing a team of data professionals.
• Excellent communication and interpersonal skills, with the ability to articulate complex technical concepts to a non-technical audience.

Preferred Qualifications

• Experience in a fast-paced, agile environment.
• Contributions to open-source data projects.
• Certifications in cloud technologies or data-related fields.
• A strong portfolio of data science and engineering projects.