{"id":27092,"url":"https://alion.io/job/pditechnologies-data-engineer-iv","title":"Data Engineer IV","company":{"id":7295,"name":"PDI Technologies","domain":"pditechnologies.com","url":"https://alion.io/company/pditechnologies","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":41000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Azure","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-07-30T11:12:50Z","employer_posted_date":"2026-07-30","last_verified_at":"2026-10-20T11:23:59Z","board_verified":true,"closed_at":null,"days_open":82,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":82},"description":"At PDI Technologies, we empower some of the world's leading convenience retail and petroleum brands with cutting-edge technology solutions that drive growth and operational efficiency.\nBy “Connecting Convenience” across the globe, we empower businesses to increase productivity, make more informed decisions, and engage faster with customers through loyalty programs, shopper insights, and unmatched real-time market intelligence via mobile applications, such as GasBuddy. We’re a global team committed to excellence, collaboration, and driving real impact. Explore our opportunities and become part of a company that values diversity, integrity, and growth.\nRole Overview:\n\nAs a Data Engineer IV, you will serve as a senior technical contributor responsible for designing, developing, and optimizing scalable cloud-based data solutions that enable enterprise analytics, reporting, and business intelligence. You will lead the delivery of complex data integration initiatives, establish engineering best practices, and provide technical guidance to other engineers. This role requires a strong understanding of modern data engineering practices and a conceptual understanding of data architecture principles to design scalable, maintainable, and governed data solutions while partnering with business and technology teams to solve complex business problems.\nKey Responsibilities\nDesign, develop, and optimize scalable cloud-based data pipelines that support enterprise analytics, reporting, and business intelligence. \nLead the development of complex data integration solutions using AWS-native technologies and modern data engineering practices. \nDesign scalable data models, ingestion frameworks, and transformation processes that support reliable, high-quality analytics. \nApply data architecture principles when designing scalable, secure, and maintainable data pipelines, data models, and integration solutions. \nEstablish and promote engineering standards, reusable frameworks, and best practices that improve platform reliability, scalability, and maintainability. \nPartner with business stakeholders to translate reporting and analytics requirements into technical solutions. \nDrive continuous improvement through automation, infrastructure as code, CI/CD, and DevOps best practices. \nLead troubleshooting and resolution of complex data platform, integration, and performance issues. \nMentor and provide technical guidance to other data engineers through code reviews, knowledge sharing, and best practice adoption. \nEvaluate emerging technologies and recommend improvements that enhance platform performance, scalability, security, and operational efficiency. \nSupport data governance initiatives by promoting data quality, metadata management, and engineering standards across the data platform.\nQualifications\nBachelor's degree in computer science, Information Technology, Engineering, or a related field, or equivalent practical experience.\n\n8+ years of experience in data engineering, cloud data platforms, or related software engineering roles.\n\nExpert experience developing cloud-based data solutions using AWS technologies such as S3, Glue, Redshift, AppFlow, Lake Formation, Step Functions, and related services.\n\nAdvanced proficiency with SQL, Python, and PySpark for developing scalable ETL/ELT solutions.\n\nPractical experience with applying AI/ML techniques to data engineering problems, such as automated data quality checks, anomaly detection, or intelligent pipeline monitoring.\n\nPractical experience developing semantic and contextual layers within a data lake house.\n\nStrong understanding of dimensional modeling, data warehousing, data lakehouse concepts, Apache Iceberg, Parquet, and modern data engineering practices.\n\nExperience integrating enterprise platforms such as Salesforce, NetSuite, and other SaaS applications.\n\nStrong understanding of modern data engineering practices with conceptual knowledge of data architecture principles, including data modeling, governance, metadata management, and scalable cloud data platforms.\n\nExperience with Infrastructure as Code (Terraform), Git, Azure DevOps, and CI/CD pipelines.\n\nDemonstrated ability to mentor engineers, influence technical decisions, and drive engineering best practices without formal people leadership.\n\nStrong analytical, problem-solving, and communication skills with the ability to collaborate across technical and business teams.\n\nBehavioral Competencies\nEnsures Accountability\n\nManages Complexity\n\nCommunicates Effectively\n\nBalances Stakeholders\n\nCollaborates 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