As a Senior Engineer in the Data Engineering & Analytics team, you will be responsible for developing high-performance data and analytics solutions. These solutions will work with vast datasets collected from various consumer-focused industries, including retail stores, restaurants, and banks. You will create algorithms, implement machine learning and AI techniques, and build intuitive workflows that help users derive valuable insights from big data to drive business decisions.

Responsibilities

• Develop and write high-quality, secure, modular, and functional code.
• Design and implement scalable data architectures and data pipelines.
• Build and optimize machine learning models and algorithms.
• Provide support to Data Scientists and other data consumers, helping them resolve data issues.
• Ensure proper data governance through validation and monitoring.
• Incorporate real-time, batch, and API-based data to enhance insights and testing.
• Innovate new approaches, tools, and techniques to solve business problems and generate insights.
• Collaborate with cross-functional teams to solve high-priority problems.
• Break complex solutions into smaller milestones, incorporating feedback from product managers and clients.
• Evangelize releases, track usage, and inform future development based on feedback.
• Continuously monitor and keep up with industry trends through learning, training, and job shadowing.

Mandatory Skills

• Proficient in Python/Scala, Spark, SQL, Hadoop (e.g., Hive, Impala), Java, and Spring Boot.
• Experience with data pipeline management tools like NIFI, Airflow.
• Experience in CI/CD practices and SQL databases (Postgres, Oracle).
• Comfortable writing shell scripts for automation and debugging.
• Solid knowledge of machine learning techniques and data engineering concepts.
• Ability to work with large, complex datasets and solve multi-layered data problems.
• Strong problem-solving and troubleshooting skills.

Nice-to-Have Skills

• Experience with cloud platforms (e.g., Azure, AWS).
• Performance tuning for databases, ETL jobs, and related scripts.
• Familiarity with Agile methodologies (e.g., Scrum).

Ideal Candidate

The ideal candidate will have a strong technical foundation in big data technologies, machine learning, and data engineering, combined with the ability to innovate and adapt to new technologies. Effective communication and collaboration skills are key for working in cross-functional teams and with diverse, distributed stakeholders.