Website:
sonyindiasoftware.co.in
Job details:
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.
Snowflake,SQL,Python,PySpark,dbt,ETL/ELT,data modeling,Git
- 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.
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