Pune || Data Architect - Mongo DB IRC257097 Hitachi Careers
Hitachi Careers
Office Location
Full Time
Experience: 8 - 8 years required
Pay:
Salary Information not included
Type: Full Time
Location: Maharashtra
Skills: SQL, relational databases, Data Migration, Data Processing, Data Cleansing, Data Enrichment, Data Privacy, data security, indexing, Performance tuning, Python, Scala, Data First systems, Data LakeData Platform projects, Data warehousing tools, NoSQL databases, orchestration tools, streamprocessing systems, data lake solutions, ETLELT processes, data governance practices, Data compliance, Data Encryption, data access controls, data audit logs, data storage optimization, data retrieval optimization, Partitioning, CICD practices, Teamwork skills, ProblemSolving Skills, Agile Model
About Hitachi Careers
Job Description
You should possess a Bachelor's degree in Computer Science, Engineering, or a related field along with at least 8 years of work experience in Data First systems. Additionally, you should have a minimum of 4 years of experience working on Data Lake/Data Platform projects specifically on AWS/Azure. It is crucial to have extensive knowledge and hands-on experience with Data warehousing tools such as Snowflake, BigQuery, or RedShift. Proficiency in SQL for managing and querying data is a must-have skill for this role. You are expected to have experience with relational databases like Azure SQL, AWS RDS, as well as an understanding of NoSQL databases like MongoDB for handling various data formats and structures. Familiarity with orchestration tools like Airflow and DBT would be advantageous. Experience in building stream-processing systems using solutions such as Kafka or Azure Event Hub is desirable. Your responsibilities will include designing and implementing ETL/ELT processes using tools like Azure Data Factory to ingest and transform data into the data lake. You should also have expertise in data migration and processing with AWS (S3, Glue, Lambda, Athena, RDS Aurora) or Azure (ADF, ADLS, Azure Synapse, Databricks). Data cleansing and enrichment skills are crucial to ensure data quality for downstream processing and analytics. Furthermore, you must be capable of managing schema evolution and metadata for the data lake, with experience in tools like Azure Purview for data discovery and cataloging. Proficiency in creating and managing APIs for data access, preferably with experience in JDBC/ODBC, is required. Knowledge of data governance practices, data privacy laws like GDPR, and implementing security measures in the data lake are essential aspects of this role. Strong programming skills in languages like Python, Scala, or SQL are necessary for data engineering tasks. Additionally, experience with automation and orchestration tools, familiarity with CI/CD practices, and the ability to optimize data storage and retrieval for analytical queries are key requirements. Collaboration with the Principal Data Architect and other team members to align data solutions with architectural and business goals is crucial. As a lead, you will be responsible for critical system design changes, software projects, and ensuring timely project deliverables. Collaboration with stakeholders to translate business needs into efficient data infrastructure systems is a key aspect of this role. Your ability to review design proposals, conduct code review sessions, and promote best practices is essential. Experience in an Agile model, delivering quality deliverables on time, and translating complex requirements into technical solutions are also part of your responsibilities.,