Sr Data Engineer (Data Warehouse-Snowflake)

IntraEdge is hiring Sr. Data Engineer (Data Warehouse-Snowflake) job in Pune | Cutshort

Sr. Data Engineer (Data Warehouse-Snowflake)
Sr. Data Engineer (Data Warehouse-Snowflake)

5
\- 11 yrs
₹5L - ₹15L / yr
Pune
Skills
SQL
snowflake
Enterprise Data Warehouse (EDW)
Python
PySpark
Sr. Data Engineer (Data Warehouse-Snowflake)
Experience: 5+yrs
Location: Pune (Hybrid)
As a Senior Data engineer with Snowflake expertise you are a subject matter expert who is curious and an innovative thinker to mentor young professionals. You are a key person to convert Vision and Data Strategy for Data solutions and deliver them. With your knowledge you will help create data-driven thinking within the organization, not just within Data teams, but also in the wider stakeholder community.
Skills Preferred
– Advanced written, verbal, and analytic skills, and demonstrated ability to influence and facilitate sustained change. Ability to convey information clearly and concisely to all levels of staff and management about programs, services, best practices, strategies, and organizational mission and values.
– Proven ability to focus on priorities, strategies, and vision.
– Very Good understanding in Data Foundation initiatives, like Data Modelling, Data Quality Management, Data Governance, Data Maturity Assessments and Data Strategy in support of the key business stakeholders.
– Actively deliver the roll-out and embedding of Data Foundation initiatives in support of the key business programs advising on the technology and using leading market standard tools.
– Coordinate the change management process, incident management and problem management process.
– Ensure traceability of requirements from Data through testing and scope changes, to training and transition.
– Drive implementation efficiency and effectiveness across the pilots and future projects to minimize cost, increase speed of implementation and maximize value delivery
Knowledge Preferred
– Extensive knowledge and hands on experience with Snowflake and its different components like User/Group, Data Store/ Warehouse management, External Stage/table, working with semi structured data, Snowpipe etc.
– Implement and manage CI/CD for migrating and deploying codes to higher environments with Snowflake codes.
– Proven experience with Snowflake Access control and authentication, data security, data sharing, working with VS Code extension for snowflake, replication, and failover, optimizing SQL, analytical ability to troubleshoot and debug on development and production issues quickly is key for success in this role.
– Proven technology champion in working with relational, Data warehouses databases, query authoring (SQL) as well as working familiarity with a variety of databases.
– Highly Experienced in building and optimizing complex queries. Good with manipulating, processing, and extracting value from large, disconnected datasets.
– Your experience in handling big data sets and big data technologies will be an asset.
– Proven champion with in-depth knowledge of any one of the scripting languages: Python, SQL, Pyspark.
Primary responsibilities
– You will be an asset in our team bringing deep technical skills and capabilities to become a key part of projects defining the data journey in our company, keen to engage, network and innovate in collaboration with company wide teams.
– Collaborate with the data and analytics team to develop and maintain a data model and data governance infrastructure using a range of different storage technologies that enables optimal data storage and sharing using advanced methods.
– Support the development of processes and standards for data mining, data modeling and data protection.
– Design and implement continuous process improvements for automating manual processes and optimizing data delivery.
– Assess and report on the unique data needs of key stakeholders and troubleshoot any data-related technical issues through to resolution.
– Work to improve data models that support business intelligence tools, improve data accessibility and foster data-driven decision making.
– Ensure traceability of requirements from Data through testing and scope changes, to training and transition.
– Manage and lead technical design and development activities for implementation of large-scale data solutions in Snowflake to support multiple use cases (transformation, reporting and analytics, data monetization, etc.).
– Translate advanced business data, integration and analytics problems into technical approaches that yield actionable recommendations, across multiple, diverse domains; communicate results and educate others through design and build of insightful presentations.
– Exhibit strong knowledge of the Snowflake ecosystem and can clearly articulate the value proposition of cloud modernization/transformation to a wide range of stakeholders.
Relevant work experience
Bachelors in a Science, Technology, Engineering, Mathematics or Computer Science discipline or equivalent with 7+ Years of experience in enterprise-wide data warehousing, governance, policies, procedures, and implementation.
Aptitude for working with data, interpreting results, business intelligence and analytic best practices.
Business understanding
Good knowledge and understanding of Consumer and industrial products sector and IoT.
Good functional understanding of solutions supporting business processes.
Skill Must have
– Snowflake 5+ years
– Overall different Data warehousing techs 5+ years
– SQL 5+ years
– Data warehouse designing experience 3+ years
– Experience with cloud and on-prem hybrid models in data architecture
– Knowledge of Data Governance and strong understanding of data lineage and data quality
– Programming & Scripting: Python, Pyspark
– Database technologies such as Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL)
Nice to have
– Demonstrated experience in modern enterprise data integration platforms such as Informatica
– AWS cloud services: S3, Lambda, Glue and Kinesis and API Gateway, EC2, EMR, RDS, Redshift and Kinesis
– Good understanding of Data Architecture approaches
– Experience in designing and building streaming data ingestion, analysis and processing pipelines using Kafka, Kafka Streams, Spark Streaming, Stream sets and similar cloud native technologies.
– Experience with implementation of operations concerns for a data platform such as monitoring, security, and scalability
– Experience working in DevOps, Agile, Scrum, Continuous Delivery and/or Rapid Application Development environments
– Building mock and proof-of-concepts across different capabilities/tool sets exposure
– Experience working with structured, semi-structured, and unstructured data, extracting information, and identifying linkages across disparate data sets
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