Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics.

What You'll Be Doing:

• Design and implement data processing systems using distributed frameworks like Hadoop, Spark, Snowflake, Airflow, or other similar technologies. 
• Build data pipelines to ingest data from various sources such as databases, APIs, or streaming platforms.
• Integrate and transform data to ensure its compatibility with the target data model or format.
• Design and optimize data storage architectures, including data lakes, data warehouses, or distributed file systems.
• Implement techniques like partitioning, compression, or indexing to optimize data storage and retrieval.
• Identify and resolve bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency.
• Design and implement data models that support efficient data storage, retrieval, and analysis.
• Collaborate with data scientists and analysts to understand their requirements and provide them with well-structured and optimized data for analysis and modeling purposes.
• Utilize frameworks like Hadoop or Spark to perform distributed computing tasks, such as parallel processing, distributed data processing, or machine learning algorithms.
• Implement security measures to protect sensitive data and ensuring compliance with data privacy regulations.
• Establish data governance practices to maintain data integrity, quality, and consistency.
• Monitor system performance, identifying anomalies, and conducting root cause analysis to ensure smooth and uninterrupted data operations.
• Communicating complex technical concepts to non-technical stakeholders in a clear and concise manner.
• Stay updated with emerging technologies, tools, and techniques in the field of big data engineering.

What We're Looking For:

• Strong analytical thinking and problem-solving skills
• Strong communication skillset – ability to translate technical details to business/non-technical stakeholders
• Extensive experience in designing and building data pipelines (ELT/ETL) for large-scale datasets. Familiarity with tools like Databricks, Apache Nifi, Apache Airflow, or Informatica is advantageous

• Proficiency in programming languages such as Python, R or Scala is essential.

• In-depth knowledge and experience with distributed systems and technologies, including On-prem Platforms, Apache Hadoop, Spark, Hive or similar frameworks. Familiarity with cloud-based platforms like AWS, Azure, or Google Cloud is highly desirable.

• Solid understanding of data processing techniques such as batch processing, real-time streaming, and data integration. Experience with data analytics tools and frameworks like Apache Kafka, Apache Flink, or Apache Storm is a plus.

• Experience with Azure Data Services - Databricks and Data Factory
• Experience with Git repository maintenance and DevOps concepts
• Familiarity with building, testing, and deploying process

• Additional certifications in big data technologies or cloud platforms are advantageous

Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.

Offer

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