Senior Data Engineer

Allegis Group; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Allegis Group is seeking a Senior Data Engineer (Senior IC / Tech Lead) in Bengaluru to design and operate enterprise data pipelines and data warehouses. You will drive end-to-end data modeling, CI/CD for data workloads, and strong collaboration with cross-functional teams to ensure scalable, secure data solutions.

You will own data quality, observability and governance while modernizing legacy ETL with dbt and cloud-native patterns.

Qualifications

• Bachelor's or master's degree in computer science, engineering, mathematics or a related discipline, or equivalent practical experience.
• Substantial professional experience designing and operating enterprise data pipelines and data warehouses in production.
• Advanced SQL skills and strong hands-on experience with Python and/or PySpark for data processing and automation.
• Deep experience with Snowflake, including performance optimization, security, workload management and scalable data modeling.
• Experience building ETL/ELT solutions with dbt, Informatica PowerCenter or comparable transformation and integration tools.
• Hands-on experience implementing CI/CD pipelines for data engineering workloads using Git-based workflows and automated testing/deployment tools.
• Experience building automated data quality systems with measurable rules, alerting, lineage and issue-resolution workflows.
• Strong grounding in data profiling, cleansing, standardization, reconciliation and production data validation.
• Ability to gather ambiguous requirements, make sound design decisions and communicate effectively with technical and non-technical partners.

Responsibilities

• Design and deliver scalable pipelines using SQL, Python and PySpark, with Snowflake as the primary data platform.
• Engineer reliable data models to support enterprise reporting and analytics.
• Own data quality with automated profiling, checks, reconciliation and lineage.
• Build CI/CD for data products with automated build, test and deployment pipelines.
• Strengthen observability and operations for pipeline health, cost and performance.
• Ingest and standardize data from databases, APIs and files with secure access patterns.
• Modernize legacy ETL by migrating to cloud-native patterns using dbt and orchestration tools.
• Translate stakeholder needs into technical designs and communicate risks and progress.
• Lead engineering practice by setting standards, reviewing designs and mentoring engineers.

Skills

Snowflake

SQL

Python

PySpark

dbt

ETL/ELT

data modeling

Git

Education

B Tech/ M Tech

Job description

Senior Data Engineer (Senior Individual Contributor / Technical Lead)

Mandatory Skills :Snowflake,SQL,Python,PySpark,dbt,ETL/ELT,data modeling,Git

Skill to Evaluate :Snowflake,SQL,Python,PySpark,dbt,ETL/ELT,data modeling,Git

Experience :6 to 8 Years

Location : Bengaluru

Job Description

Required qualifications

• Bachelor's or master's degree in computer science, engineering, mathematics or a related discipline, or equivalent practical experience.
• Substantial professional experience designing and operating enterprise data pipelines and data warehouses in production.
• Advanced SQL skills and strong hands-on experience with Python and/or PySpark for data processing and automation.
• Deep experience with Snowflake, including performance optimization, security, workload management and scalable data modeling.
• Experience building ETL/ELT solutions with dbt, Informatica PowerCenter or comparable transformation and integration tools.
• Hands-on experience implementing CI/CD pipelines for data engineering workloads using Git-based workflows and automated testing/deployment tools.
• Experience building automated data quality systems with measurable rules, alerting, lineage and issue-resolution workflows.
• Strong grounding in data profiling, cleansing, standardization, reconciliation and production data validation.
• Ability to gather ambiguous requirements, make sound design decisions and communicate effectively with technical and non-technical partners.

Preferred qualifications

• Snowflake SnowPro Core or comparable cloud data certification.
• Experience with REST API, event and/or streaming data, and high-volume security or operational datasets.
• Familiarity with data observability and quality frameworks such as dbt tests, Great Expectations, Soda or Deequ.
• Experience delivering data solutions in regulated, security-sensitive, healthcare, telecommunications or audit-oriented environments.
• Demonstrated technical leadership, mentoring or delivery coordination across a small engineering team.

Education Qualificaiton : B Tech/ M Tech

Job Title : Senior Data Engineer (Senior Individual Contributor / Technical Lead)

Roles & Responsibilities

• Design and deliver scalable pipelines. Build batch and near-real-time ETL/ELT pipelines using SQL, Python and PySpark, with Snowflake as a primary cloud data platform.
• Engineer reliable data models. Create dimensional, normalized and analytical models that support efficient querying, traceability and reuse across enterprise reporting and analytics.
• Own data quality by design. Implement automated profiling, schema checks, reconciliation, completeness, freshness, uniqueness and business-rule validation; publish quality results and route failures for action.
• Build CI/CD for data products. Create and maintain automated build, test and deployment pipelines for SQL, dbt, orchestration code and infrastructure configuration, including version control, peer review, environment promotion and safe rollback.
• Strengthen observability and operations. Monitor pipeline health, lineage, cost, performance and service-level objectives; troubleshoot incidents, perform root-cause analysis and eliminate recurring manual support.
• Integrate diverse sources. Ingest and standardize data from databases, APIs, files and event sources, applying secure access patterns and appropriate handling for sensitive information.
• Modernize legacy workflows. Migrate or refactor Informatica PowerCenter and other legacy ETL processes into maintainable cloud-native patterns using tools such as dbt and modern orchestration platforms.
• Partner from requirement to adoption. Translate stakeholder needs into technical designs, validate production outcomes and communicate tradeoffs, risks and delivery progress clearly.
• Lead through engineering practice. Set coding and testing standards, review designs and pull requests, mentor engineers and coordinate delivery across cross-functional teams.