Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Data Engineering
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
We are looking for a highly skilled Data Engineer experienced with SQL, Python, dbt, and cloud based data pipelines. The role requires strong analytical skills, deep understanding of data warehousing, and hands on experience building reliable, scalable, production grade data systems. You will work across ingestion, transformation, automation, and observability layers, ensuring data quality and platform resilience.
Roles & Responsibilities:
-Build & maintain scalable batch/incremental pipelines across cloud, DWH, and APIs
-Design and optimize dbt models, tests, and deployment workflows
-Implement dimensional models, SCDs, CDC, and data quality frameworks
-Troubleshoot production issues across SQL, pipelines, cloud services
-Develop automation and CI/CD workflows for data transformations
-Contribute reusable tooling, templates, code standards, and documentation
-Collaborate with platform, analytics, and product teams for high quality datasets
Must to Have:
SQL & RDBMS
-Strong SQL with complex joins, window functions, CTEs, and incremental/CDC patterns
-MERGE based upserts, partitioning, data type conversions
-Indexing fundamentals, query tuning, and handling large datasets
Data Warehousing
-Fact/dimension modelling, star/snowflake schema
-SCD Type 1 & 2, surrogate keys, grain definition
-Full vs incremental loads, CDC concepts, data quality checks
Troubleshooting & Analytical Skills
-Production data pipeline debugging (logs, distributed systems, cloud components)
-SQL/data warehouse performance investigation
-Root cause analysis and preventive fix implementation
dbt (Core & Cloud)
-Hands on with models, incremental strategies, tests, snapshots
-dbt Cloud jobs, environment mgmt., Git/CI integration
-Ensuring reliable, optimized, lineage aware transformations
Cloud Foundations
-Core cloud concepts (IaaS/PaaS/SaaS), object storage, compute, IAM
-Serverless & container fundamentals
-Monitoring/logging tools and basic networking (VPC/subnets/security groups)
Python for Data Engineering
-File handling, API integration, JSON/YAML parsing
-Logging, error/exception handling
-boto3, basic pandas, modular coding, virtual envs, dependency mgmt
CI/CD
-Building testable, automated deployment pipelines
-Git workflows, environment promotion, code quality gates
Good to Have:
Snowflake
-Stages, Storage Integrations, Pipes
-Streams, Tasks, Dynamic Tables
-Query profiling, clustering, warehouse optimization
AWS
-S3 (encryption, cross account access, notifications, lifecycle)
-DMS, Lambda (ECR based), IAM fundamentals
-VPC/Subnet/SG concepts, CloudWatch troubleshooting, ECS basics
GitLab, DevOps & IaC
-Pipeline design, variables/secrets, artifacts
-Docker basics, Terraform for provisioning
Kafka / Confluent
-Producers, consumers, topics, partitions
-Schema evolution, streaming DWH integrations
-Monitoring/troubleshooting streaming workloads
Airflow (Astronomer)
-DAG design, dependencies, retries, backfills
-Integrations with cloud storage, DWHs, APIs
-Logging, observability, and failure recovery
Professional & Technical Skills:
-Advanced SQL and data modelling
-dbt Core/Cloud expertise
-Python (APIs, boto3, logging, modular packages)
-Cloud compute, IAM, object storage, observability
-CI/CD pipeline development
-Preferred: Snowflake, AWS, Kafka, Airflow, GitLab, Docker, Terraform
Additional Information:
-Minimum 4 years of hands-on experience in Data Engineering space
-Location: Primary : Bengaluru and Secondry : Pune
-Education: 15 years of full-time education required, Engineering Degree preferable
Bengaluru
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