A leading consulting firm in Chennai is seeking a Data Engineer with 3 to 5 years of experience in data engineering, data warehousing, or related fields. The role involves designing and maintaining scalable data pipelines, collaborating with teams on data models, and ensuring data quality and accuracy. The ideal candidate must have strong SQL and NoSQL skills, proficiency in ETL tools and BigQuery, and experience with cloud platforms like Google Cloud. This is an exciting opportunity for data professionals looking to grow their careers.
Qualifications
3 to 5 years of experience in data engineering or related field.
Experience with dashboarding tools like Looker Studio and building data pipelines.
Familiarity with NoSQL and distributed database management systems.
Responsibilities
Design, implement, and maintain scalable data pipelines.
Collaborate with teams to design and implement data models.
Implement data quality checks to ensure data accuracy.
Skills
SQL
NoSQL
ETL tools
BigQuery
Python
Data modeling techniques
Troubleshooting
Collaborative skills
Tools
Cloud SQL
Terraform
Data Flow
Data Proc
Airflow
Job description
Job description
Experience
Experience level of 3 to 5 years in data engineering, data warehousing, or a related field.
Experience with dashboarding tools like plx dashboard and looker studio Experience with building data pipelines, reports, best practices and frameworks.
Experience with design and development of scalable and actionable solutions (dashboards, automated collateral, web applications).
Experience with code refactoring for optimal performance.
Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources.
Familiarity with non-relational data storage systems (NoSQL and distributed database management systems).
Skills
Strong proficiency in SQL, NoSQL, ETL tools, BigQuery and at least one programming language (e.g., Python, Java).
Big Query,Data Flow,Data Proc,Cloud Sql,Teraform etc
Strong understanding of data structures, algorithms, and software design principles.
Experience with data modeling techniques and methodologies.
Proficiency in troubleshooting and debugging complex data-related issues.
Ability to work independently and as part of a team.
Responsibilities
Data Pipeline Development: Design, implement, and maintain robust and scalable data pipelines to extract, transform, and load data from various sources into our data warehouse or data lake.
Data Modeling and Warehousing: Collaborate with data scientists and analysts to design and implement data models that optimize query performance and support complex analytical workloads.
Cloud Infrastructure: Leverage Google Cloud and other internal storage platforms to build and manage scalable and cost-effective data storage and processing solutions.
Data Quality Assurance: Implement data quality checks and monitoring processes to ensure the accuracy, completeness, and consistency of data.
Build large scale data and analytics solutions on GCP, Efficiently use the GCP platform to integrate large datasets from multiple data sources, analyse data, data modelling, data exploitation/visualization, DevOps, CI/CD implementation Build automated data pipelines and work in Data engineering solution on GCP using Cloud BigQuery, Cloud DataProc,
Performance Optimization: Continuously monitor and optimize data pipelines and queries for performance and efficiency.
Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand their data needs and deliver solutions that meet their requirements.
Desirable
Experience Cloud Storage or equivalent cloud platforms
Knowledge of BigQuery ingress and egress patterns
Experience in writing Airflow DAGs
Knowledge of pubsub,dataflow or any declarative data pipeline tools using batch and streaming ingestion