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49 Discovery Channel Jobs

Senior Software Engineer - Data Test Automation

Discovery Channel

5-8 years

Hyderabad / Secunderabad

1 vacancy

Discovery Channel

posted 2mon ago

Job Role Insights

Key skills for the job

Data Analysis Data Analytics Python SQL Clinical Data Management Informatica

+ 3 more

Job Description

Data Validation and Testing: Expertise in validating data quality, integrity, and consistency across different datasets.
SQL and Database Knowledge: Proficiency in SQL for querying and validating data in various types of databases (relational and non-relational).
Programming Languages: Knowledge of programming languages like Python or R, particularly for data manipulation, automation, and building custom validation scripts.
Engineering - Build systems and datasets to meet Data Quality objectives, using software engineering, data management, and operational best practices.
Analysis and Design - Analyze systems and data to identify data quality gap, data patterns, Detect anomalies and provide solutions. Design and document data models and transformation specifications.
Data Warehousing: Understanding of data warehousing concepts, ETL processes, and tools (e.g., Apache Airflow, Talend).
Data Quality Tools: Familiarity with tools like Apache Spark, Pandas, Great Expectations, Informatica Data Quality, Talend Data Quality, etc.
Big Data Technologies: Experience with big data frameworks like Hadoop, Apache Spark, and distributed computing environments.
API Testing: Skills in testing and validating data flows through APIs and web services.
Data Governance and Compliance: Knowledge of data governance frameworks, data privacy
Tooling Aptitude- Successful track record of instrumenting tools, automation, and processes at scale for frontend and backend Quality engineering activities (Unit, Integration, User journey, Load, payment, regression testing)
Software Quality - Understanding of automation workflows, CICD release pipelines, test environments across multiple products and release within an agile development framework.
Effectively communicate - through technical documentation, and experience using various tools and technologies such as JIRA, Confluence, GitHub.
Partner across Teams - Partner with analysts, engineers, subject matter experts, and product managers to apply WBD s analytical and quality methods to satisfy stakeholder needs.
Improvement Driven - Experience working with DevOps teams to drive improvements in Release Tools pipeline for automated tracking and reporting on release artifacts: JIRA items, sprint scope, bug report, test report, release notes.

What to Bring:

5+ years of hands-on software and quality engineering experience focused on Data Platform & Analytics
5+ years of hands-on experience in Data Validation, building custom validation scripts and automation Data Validation pipelines
Proficiency in SQL, Data Warehousing, Data Analysis, Data Profiling and Governance concepts
Hands-on experience testing large-scale, production systems using Python, SQL, Apache Spark and Open Source Data Platform Validation Tools
Experience working with public cloud infrastructure (AWS, GCP, Azure)
AWS - 2+ years of experience with AWS Cloud Data Technologies including familiarity with EMR, Kinesis, Athena
In-depth knowledge and understanding of standard quality best practices, techniques and methodologies to drive continuous quality improvements
Ability to take a project from scoping the requirements and building the test cases
Experience with continuous integration / continuous deployment systems like Jenkins
Familiarity with Gen AI based test automation, models, processes and tools