Senior Consultant

4 weeks ago


BangaloreGurgaonGurugramPuneChennaiKolkata, India VIDPRO CONSULTANCY SERVICES Full time

Primary Roles and Responsibilities :

- Developing Modern Data Warehouse solutions using Databricks and Azure Stack

- Ability to provide solutions that are forward-thinking in data engineering and analytics space

- Collaborate with DW/BI leads to understand new ETL pipeline development requirements.

- Triage issues to find gaps in existing pipelines and fix the issues

- Work with business to understand the need in reporting layer and develop data model to fulfill reporting needs

- Help joiner team members to resolve issues and technical challenges.

- Drive technical discussion with client architect and team members

- Orchestrate the data pipelines in scheduler via Airflow Skills

Qualifications :

- Must have a total 4+ yrs. of IT experience experience in Data warehouse/ETL projects.

- Deep understanding of Star and Snowflake dimensional modeling.

- Strong knowledge of Data Management principles

- Good understanding of Databricks Data & AI platform ans ADB

- Should have hands-on experience in SQL, Python and Spark (PySpark)

- Candidate must have experience in Azure stack

- Desirable to have ETL with batch and streaming (Kinesis).

- Experience in building ETL / data warehouse transformation processes

- Experience working with structured and unstructured data including imaging & geospatial data.

- Experience working in a Dev/Ops environment with tools such as Terraform, CircleCI, GIT.

- Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning and troubleshoot

- Databricks Certified Data Engineer Associate/Professional Certification (Desirable).

- Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects

- Should have experience working in Agile methodology

- Strong verbal and written communication skills.

- Strong analytical and problem-solving skills with a high attention to detail.

Mandatory Skills : / PySpark / Spark with Azure/Databricks/SQL/Python/Azure Datafactory

(ref:hirist.tech)

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