Senior Data Engineer

Flipkart Group; Bengaluru; Presencial; INR 1.100.000 - 2.100.000; Tempo integral

Resumo da vaga

Flipkart Group is hiring a seasoned Data Engineer to tackle large-scale data problems, focusing on data modelling, ETL pipelines, and data warehousing. You will collaborate with analytics, engineering, and business teams to deliver scalable data solutions that enable informed decision-making.

The role emphasizes strong SQL, Python/PySpark, and experience with Airflow and cloud data platforms to optimise data processing and reporting. Join a cross-functional team driving revenue-focused insights.

Qualificações

• 5+ years of experience in Data Engineering with hands-on data pipelines and data warehouse expertise.
• Strong understanding of data modelling principles including dimensional modelling and normalisation.
• Strong SQL ability to analyse and optimise complex queries and workloads.
• Strong analytical and problem-solving skills to translate requirements into scalable data solutions.

Responsabilidades

• Partner with stakeholders to understand data, reporting, and business needs.
• Collaborate with engineering to collect and integrate data from systems.
• Design scalable data models and robust ETL/ELT pipelines.
• Develop and maintain ETL workflows using Airflow.
• Implement automated data quality checks for accuracy and reliability.
• Work with Snowflake, Redshift, and distributed data systems for warehousing.
• Perform SQL and ETL performance tuning to optimise processing.
• Utilise Python, PySpark, Spark, Databricks for large-scale data processing.
• Support business teams with data-driven insights and KPI reporting.
• Participate in Agile/Scrum ceremonies with cross-functional teams.

Conhecimentos

Data modeling

SQL optimization

Python

PySpark

Airflow

Databricks

Snowflake

ETL pipelines

Data warehousing

Ferramentas

Snowflake

Amazon Redshift

Databricks

Descrição da vaga

Work on large-scale data engineering problems involving data modelling, ETL pipelines, data warehousing, orchestration, and performance optimisation. You'll collaborate with engineering, analytics, infrastructure, and business teams to build scalable data solutions that directly support business decision-making and revenue initiatives.

Responsibilities:

• Partner with technical and non-technical stakeholders to understand data, reporting, and business requirements.
• Work with engineering teams to collect and integrate data from internal and external systems.
• Design scalable and performant data models, including dimensional modelling and database normalisation.
• Design and develop robust ETL/ELT pipelines and define appropriate data integration strategies.
• Develop and maintain ETL workflows using orchestration tools such as Apache Airflow.
• Build and implement automated Data Quality checks to ensure accuracy, consistency, and reliability of data.
• Work with relational databases and distributed data systems such as Snowflake or Amazon Redshift.
• Perform advanced SQL and ETL performance tuning to optimise data processing and query performance.
• Work with technologies such as Python, PySpark, Spark, Databricks, Snowflake or EMR for large-scale data processing.
• Implement database deployments and schema changes using tools such as Schema Change.
• Build and report on business KPIs and metrics within data warehousing environments.
• Perform ad hoc data analysis and support business teams with data-driven insights.
• Participate in Agile/Scrum ceremonies and collaborate closely with cross-functional engineering and analytics teams.

Requirements:

• 5+ years of experience in Data Engineering with strong hands-on experience building data pipelines and data warehouse solutions.
• Strong understanding of data modelling principles, including dimensional modelling and normalisation.
• Strong SQL expertise with the ability to analyse and optimise complex queries and data workloads.
• Strong analytical and problem-solving skills with the ability to translate business requirements into scalable data solutions.