We are looking for a Big Data Developer who loves solving complex problems across a full spectrum of technologies. He/she will help ensure technological infrastructure operates seamlessly in support of our business objectives.
- Ability to take lead and work in a trustworthy working environment.
- Partner with the required teams and get seamless outputs.
- Should be curious to learn more and collaborate whenever needed.
- Ability to independently manage projects and report/present efforts to clients.
- Strong communication skills.
- Select and integrate any Big Data tools and frameworks required to provide requested capabilities.
- Develop and implement data pipelines that extracts, transforms and loads data into an information product that helps to inform the organization in reaching strategic goals.
- Work on ingesting, storing, processing and analyzing large data sets.
- Create scalable and high-performance web services for tracking data.
- Work closely with a data science team implementing data analytic pipelines.
- Customize and manage integration tools, databases, warehouses, and analytical systems.
- Translate complex technical and functional requirements into detailed designs.
- Investigate and analyze alternative solutions to data storing, processing etc. to ensure most streamlined approaches are implemented.
- Help define data governance policies and support data versioning processes.
- Maintain security and data privacy working closely with Data Protection Officer internally.
- Degree in computer sciences, math or engineering.
- Proficient understanding of distributed computing principles.
- Proficiency with Hadoop v2, MapReduce, HDFS.
- Experience in Python, Spark and Hive.
- Experience with NoSQL databases, such as HBase, Cassandra, MongoDB.
- Experience with various messaging systems, such as Kafka or RabbitMQ.
- Experience with integration of data from multiple data sources.
- Strong data engineering skills on the Azure Cloud Platform is essential.
- Understanding of data warehousing and data modeling techniques.
- Knowledge of various ETL techniques and frameworks, such as Flume.
- Knowledge of industry-wide analytical and visualization tools (Tableau and R).
- Knowledge of core Java, Linux, SQL, and any scripting language.