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Job Location: Hyderabad/Secunderabad
JR21713 Big Data – Hadoop, Spark (Engineer/Sr Engineer), SMAI
Our vision is to transform how the world uses information to enrich life. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
Responsibilities and Tasks
Understand the Business Problem and the Relevant Data
- Maintain an intimate understanding of company and department strategy
- Translate analysis requirements into data requirements
- Identify and understand the data sources that are relevant to the business problem
- Develop conceptual models that capture the relationships within the data
- Define the data-quality objectives for the solution
- Be a subject matter expert in data sources and reporting options
Architect Data Management Systems
- Use understanding of the business problem and the nature of the data to select appropriate data management system (Big Data, Cloud DW,Cloud (GCP/AWS/Azure), OLTP, OLAP, etc.)
- Design and implement optimum data structures in the appropriate data management system (Cloud DW, Cloud (GCP/AWS/Azure), Hadoop, SQL Server/Oracle, etc.) to satisfy the data requirements
- Plan methods for archiving/deletion of information
Develop, Automate, and Orchestrate an Ecosystem of ETL Processes for Varying Volumes of Data
- Identify and select the optimum methods of access for each data source (real-time/streaming, delayed, static)
- Determine transformation requirements and develop processes to bring structured and unstructured data from the source to a new physical data model
- Develop processes to efficiently load the transform data into the data management system
Prepare Data to Meet Analysis Requirements
- Work with the data scientist to implement strategies for cleaning and preparing data for analysis (e.g., outliers, missing data, etc.)
- Develop and code data extracts
- Follow standard methodologies to ensure data quality and data integrity
- Ensure that the data is fit to use for data science applications
Qualifications and Experience:
- 2 – 8 years of experience developing, delivering, and/or supporting data engineering, advanced analytics or business intelligence solutions
- Experienced in developing ETL/ELT processes using Apache Ni-Fi and Snowflake
- Significant experience with big data processing and/or developing applications and data sources via Hadoop, Yarn, Hive, Pig, Sqoop, MapReduce, HBASE, Flume, etc.
- Significant experience with big data processing and/or developing applications and data Pipelines via Hadoop, Yarn, Hive, Spark, Pig, Sqoop, MapReduce, HBASE, Flume, etc.
- Data Engineering and Analytics on Google Cloud Platform using BigQuery, Cloud Storage, Cloud SQL, Cloud Pub/Sub, Cloud DataFlow, Cloud Composer..etc or equivalent cloud platform.
- Familiarity with software architecture (data structures, data schemas, etc.)
- Strong working knowledge of databases (Oracle, MSSQL, etc.) including SQL and NoSQL.
- Strong mathematics background, analytical, problem solving, and organizational skills
- Strong communication skills (written, verbal and presentation)
- Experience working in a global, multi-functional environment
- Minimum of 2 years’ experience in any of the following: At least one high-level client, object-oriented language (e.g. JAVA/Python/Perl/Scala, etc.); at least one or more web programming language (PHP, MySQL, Python, Perl, JavaScript etc.); one or more Data Extraction Tools (Apache NiFi/Informatica/Talend etc.)
- Software development using programming languages like Python/Java/Scala
- Ability to travel as needed
Good To have:
- Cloud Certification in GCP/AWS/Azure
- Machine Learning concepts
Education:
B.S. degree in Computer Science, Software Engineering, Electrical Engineering, Applied cmatics or related field of study.
M.S. degree preferred.
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