Senior Data Engineer
4 days ago• Bangalore, India
Does working with data on a day-to-day basis excite you? Are you interested in building robust data architecture to identify data patterns and optimize data consumption for our customers, who will forecast and predict what actions to undertake based on data? If this is what excites you, then you'll love working in our Data Analytics team.
We are looking for a savvy Data Engineer to join our growing team of AI , BI and machine learning experts. You will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The Data Engineer will support our software engineers, data analysts, dashboard developers and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.
Responsibilities
- Create and maintain optimal data pipeline architecture; assemble large, complex data sets that meet functional / non-functional requirements.
- Design the right schema to support the functional requirement and consumption pattern.
- Design and build production data pipelines from ingestion to consumption.
- Build the necessary datamarts, data warehouse required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
- Create necessary preprocessing and postprocessing for various forms of data for training/ retraining and inference ingestions as required
- Create data visualization and business intelligence tools for stakeholders and data scientists for necessary business/ solution insights
- Identify, design, and implement internal process improvements: automating manual data processes, optimizing data delivery, etc.
- Ensure our data is separated and secure across national boundaries through multiple data centers and AWS regions.
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Requirements and Skills
- You should have a bachelor's or master's degree in computer science, Information Technology or other quantitative fields
- You should have at least 5 years working as a data engineer in supporting large data transformation initiatives related to machine learning, with experience in building and optimizing pipelines and data sets
- Strong analytic skills related to working with unstructured datasets.
Must-have Programming Skills:
- Significant programming experience python programming, spark is must.
- Good Hands -on experience in SQL, writing analytical queries and windows functions.
- Good Hands - on experience in creating external tables, partitioning, parquet files.
- 3-5 years of solid experience in Big Data technologies a must.
- Data Engineering experience using AWS core services (Lambda, Glue, EMR and RedShift)
- Knowledge of Python and Pyspark is an absolute must.
Requirements/Skill sets:
- Knowledge of Database Concepts - Indexing, Partitioning is must.
- Knowledge of Data warehousing - Normalization, Denormalization, Star/Snow-flake schemas.
- Good Hands -on the table's creations, DDL, DML and TCL
- Hands on experience in Informatica PowerCenter/IICS as an ETL tool
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift, S3, Athena and familiarity with various log formats from AWS.
- Experience with object-oriented/object function scripting languages: Python, Pyspark
- Experience in, Dbeaver tool, AWS Glue ETL, AWS Crawler, AWS Lambda, Glue Data Catalog, AWS Glue Studio.
Good to Have Skill sets:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with data pipeline and workflow management tools: Airflow, Luigi etc.
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- You should be a good team player and committed for the success of team and overall project.
Requirements/Skill sets:
- Knowledge of Database Concepts - Indexing, Partitioning is must.
- Knowledge of Data warehousing - Normalization, Denormalization, Star/Snow-flake schemas.
- Good Hands -on the table's creations, DDL, DML and TCL
- Hands on experience in Informatica PowerCenter/IICS as an ETL tool
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift, S3, Athena and familiarity with various log formats from AWS.
- Experience with object-oriented/object function scripting languages: Python, Pyspark
- Experience in, Dbeaver tool, AWS Glue ETL, AWS Crawler, AWS Lambda, Glue Data Catalog, AWS Glue Studio.
Good to Have Skill sets:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with data pipeline and workflow management tools: Airflow, Luigi etc.
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- You should be a good team player and committed for the success of team and overall project.
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Client-provided location(s): Bangalore, India
Job ID: Schneider_Electric-https://careers.se.com/jobs/95384?lang=en-us
Employment Type: FULL_TIME
Posted: 2025-07-30T23:43:30
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion