Job Description
Role: Sr Data Architect (Google Cloud Platform)
Location: Remote...
Duration: 12+ Months
Key responsibilities:
Lead the requirement gathering process and create comprehensive technical designs (high-level and detailed).
Develop a robust data ingestion framework for diverse data sources.
Participate actively in architectural discussions, perform system analysis (reviewing existing systems and operational methodologies), and analyze emerging technologies to propose optimal solutions that address current needs and simplify future modifications.
Design data models suitable for transactional and big data environments, serving as input for machine learning processing.
Design and build the necessary infrastructure to enable efficient ETL from various data sources, leveraging Google Cloud Platform services.
Develop data and semantic interoperability specifications.
Collaborate with the business to define and scope project requirements.
Partner with external vendors to facilitate data acquisition.
Analyze existing systems to identify suitable data sources.
Implement and continuously improve data automation processes.
Champion continuous improvement in DevOps automation.
Provide design expertise in Master Data Management, Data Quality, and Meta Data Management.
Required Skills:
Active Google Cloud Data Engineer or Google Professional Cloud Architect Certification.
Minimum 8 years of experience designing, building, and operationalizing large-scale enterprise data solutions and applications using Google Cloud Platform data and analytics services alongside 3rd party tools (Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache Beam/Composer, BigTable, Cloud BigQuery, Cloud Pub/Sub, Cloud Storage, Cloud Functions, & Github).
Minimum 5 years of experience performing detailed assessments of current data platforms and crafting strategic migration plans to Google Cloud Platform cloud.
Strong Python development experience (mandatory).
2+ years of data engineering experience with distributed architectures, ETL, EDW, and big data technologies.
Demonstrated knowledge and experience with Google Cloud BigQuery (mandatory).
Experience with DataProc & DataFlows using Java on Google Cloud Platform.
Experience with serverless data warehousing concepts on Google Cloud.
Experience with DWBI modelling frameworks.
Strong understanding of Oracle databases and familiarity with GoldenGate is highly desired.
Expertise in Debezium and Apache Flink for change data capture and processing.
Experience working with both structured and unstructured data sources using cloud analytics platforms (e.g., Cloudera, Hadoop).
Experience with Data Mapping and Modelling.
Experience with Data Analytics tools.
Proven proficiency in one or more programming/scripting languages: Python, JavaScript, Java, R, UNIX Shell, php, or ruby.
Experience with Google Cloud services: Streaming + Batch, Cloud Storage, Cloud Dataflow, DataProc, DFunc, BigQuery, BigTable.
Knowledge and proven use of contemporary data mining, cloud computing, and data management tools: Microsoft Azure, AWS Cloud, Google Cloud, Hadoop, HDFS, MapR, and Spark.
Bachelor's degree or equivalent (minimum 12 years) work experience.
Arvind Kumar Bind
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