Discover Dollar Technologies - Manager - Data Operations (6-10 yrs)

The Manager - Data Operations will focus on data engineering and data science to optimize our data practices and decision-making systems. This role will lead ETL processes, data pipeline development, and advanced analytics efforts, with a strong emphasis on Generative AI, working with large datasets. You will drive business insights, enable advanced analytics, and develop sustainable solutions that support the company's strategic goals.

Roles and Responsibilities :

- Team Development and Leadership : Build and mentor high-performing data engineering, data science and data analysis teams by promoting a collaborative, open, and growth-oriented culture.

- Strategic Planning : Define the strategy and roadmap for the Discover Dollar data platform, ensuring alignment with business and technological objectives.

- System Architecture : Design and implement scalable, fault-tolerant distributed systems for data ingestion, processing, and analytics.

- Cross-Functional Collaboration : Partner with product, business, and data science teams to gather requirements, prioritize tasks, and develop impactful solutions.

- Hands-On Problem Solving : Contribute to coding when necessary to resolve complex challenges or provide architectural insights.

- Operational Excellence : Advocate for and implement best practices in software development, deployment, monitoring, and incident management.

- Innovation and Growth : Drive initiatives to adopt emerging technologies and enhance the capabilities of the Discover Dollar data platform.

- Project Ownership : Take full ownership of projects, ensuring high quality, scalability, and timely delivery.

Technical Expertise :

- Data Engineering and Architecture : Proficient in ETL processes, analytical platforms, and event-driven architectures.

- Programming Proficiency : Advanced knowledge of Python, Pyspark and SQL, with a strong understanding of distributed data systems.

- Pipeline Design : Experienced in creating real-time and batch data pipelines using tools like Kafka, Spark, Azure Data Factory, and Databricks and Azure Synapse Analytics.

- Cloud and DevOps Tools : Hands-on experience with cloud platforms such as Azure, along with tools like Docker.

- DataOps and Data Governance : Well-versed in DataOps and Version Control and data governance platforms like Unity Catalog.

Education & Experience :

- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.

- 6+ years of experience in data engineering, analytics, or related fields.

- Strong expertise in ETL processes, SQL, Python, Spark and cloud-based data solutions.

- Proficiency in data warehousing solutions, including Azure, Redshift, Snowflake, or similar.

- Solid understanding of API development and integration.

- Strong problem-solving and communication skills, with the ability to collaborate across cross-functional teams.

- Experience with advanced machine learning models and deployment strategies.