{"id":1274975,"url":"https://alion.io/job/paynet-data-resiliency-engineer-data-lake","title":"Data Resiliency Engineer - Data Lake","company":{"id":2112342,"name":"PayNet","domain":"paynet.my","url":"https://alion.io/company/paynet-my","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BrioHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14500,"max_usd":42000,"period":"year","method":null,"sample_n":3503},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Datadog","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Incident Management","optional":false},{"name":"Kubernetes","optional":false},{"name":"Opsgenie","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-26T01:11:32Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-09-29T16:48:13Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"SUMMARY OF RESPONSIBILITIES\nAs a Data Resiliency Engineer, you will be at the forefront of maintaining and enhancing the robustness of our data infrastructure. You will analyze issues to identify root causes and implement solutions that ensure a seamless user experience. Your expertise in data ecosystem monitoring, incident management, and data quality enhancement will play a pivotal role in maintaining operational excellence. You will utilize advanced tools like Datadog and Opsgenie to proactively monitor and resolve issues, act as a subject matter expert for data-related inquiries, and champion data quality initiatives. Additionally, you will work closely with the team to ensure our suite of payments reporting systems for participants as well as PayNet internal reports, are accurate and aligned with evolving organizational needs, driving continuous improvement in our data-driven operations.\nKEY AREAS OF RESPONSIBILITIES\nRoot Cause Analysis & Bug Fixing: Analyze issues to uncover root causes and implement effective solutions, ensuring a smooth user experience.\nData Ecosystem Monitoring: Oversee the data environment using advanced monitoring tools like Datadog, proactively identifying and addressing issues before they escalate.\nAlert System Management: Collaborate with the team managing Opsgenie and other alert systems, ensuring timely responses to critical incidents and maintaining operational excellence.\nData Lake Support: Serve as the primary contact for data-related inquiries, including ETL incident management, reporting challenges, and providing actionable insights.\nData Quality Monitoring: Own and enhance data quality monitoring tools, designing robust pipelines and frameworks to maintain the highest data integrity standards.\nReporting Management: Lead report amendments and ensure reporting processes are accurate and meet the evolving needs of the organization.\nQUALIFICATIONS & EXPERIENCE\nMinimum Qualifications\nBachelor's degree in Computer Science, Engineering, Information Systems, or a related field.\nStrong experience with AWS data services (e.g., S3, Glue, Athena, Quicksight, Lambda).\nStrong experience in Python programming language\nProficiency in PySpark for large-scale data processing.\nFamiliarity with workflow management tools (e.g., Apache Airflow)\nFamiliarity with operating data tools on Kubernetes and EKS\nExpertise in monitoring tools (e.g., Datadog, CloudWatch) to proactively track and resolve issues.\nExperience with alert management systems like Opsgenie or similar platforms.\nStrong understanding of data lakes and managing large-scale data environments.\nExperience in performing root cause analysis for complex data issues and implementing effective bug fixes.\nTerraform or other IaC tools for infrastructure provisioning\nRelevant certifications in AWS and data engineering\nPERSONAL QUALITIES\nSelf-motivated problem solver who can work with minimal guidance\nExcellent communication skills to articulate technical details clearly to non-technical stakeholders.\nDetail-oriented with a focus on data quality and reliability\nProven ability to work cross-functionally with multiple teams (e.g., Data Engineering, Operations, Analytics).\nPassionate engineer looking to learn new technologies","description_format":"text","description_chars":3248,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-26T01:11:32Z"}],"liveness":{"score":81,"band":"hot","label":"Hiring now","p_open":0.9,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":21,"reasons":["conf:63","velocity","win:early"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/paynet-data-resiliency-engineer-data-lake","json_url":"https://alion.io/job/paynet-data-resiliency-engineer-data-lake.json","meta":{"generated_at":"2026-09-30T04:13:23Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2868,"day_limit":5000,"remaining_today":2132,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}