Assistant Manager DI - Data Engineer

Job Purpose:

Design and build the evolution of Zong in-house Data Middle Platform/DWH, enabling Intelligent Cockpits, Campaign Management Systems, AI/ML models, and all data-driven operational and commercial platforms. This role owns the models, ETL pipelines, and governance alignment.

Job Responsibilities:

1. Data Engineering & Pipelines: Design and operate robust ETL/ELT and streaming pipelines from all domains, apps, network systems, and external sources into Hadoop, Teradata, GaussDB and Object Storage. Implement enterprise-grade data quality, reconciliation, and validation frameworks within pipelines. Own release management for data deployments: versioned datasets, lineage, rollback procedures, and impact analysis. Ensure pipelines are secure, governed, SLA-driven, and automation-first.

2. Data Products, Enablement & Intelligence Consumption: Build curated subject areas, marts, and semantic layers for: - Commercial analytics - Churn & precision marketing - Stock-base & franchise performance - Network & experience analytics Develop data products and reusable datasets consumed by: - Intelligent Cockpits - Campaign Management Platforms - AI/ML models - IOP and operational systems Design feature-ready datasets for AI/ML teams (training, inference, real-time scoring). Ensure all-consuming systems use standardized, governed, reusable data services not one-off extracts.

3. Telecom Domain & Business Alignment: Apply strong understanding of Telecom O/B/M/P domains: - OSS (Network, QoS, Events) - BSS (CRM, Billing, Charging, Campaigns) - MSS (Finance, HR, Supply Chain) - Public ( Social Media, unstructured data etc.) Design models and pipelines that reflect real telecom business logic, KPIs, and operational flows. Work closely with Commercial, CX, Network, Finance, and AI teams to translate use cases into platform capabilities.

4. Data Governance, Standards & Platform Maturity: Work within the enterprise Data Governance Framework (quality, lineage, metadata, security, access, stewardship). Partner with Governance, Security and Compliance teams to ensure: - Trusted datasets - Controlled access - Auditability & lineage Help mature the organization from reporting → analytics → AI-driven decisioning.

Eligibility Criteria (Education, Knowledge, Experience and Skills):

Education:

• Must have a Bachelor's degree or above, preferably in Computer Science / Engineering
• Certification in Data Management will be preferred. ,

Work Experience:

Upto 5-7 years of relevant experience, preferably in Data Engineering/ Analytics

Skills – Generic:

• Should be passionate about data, data management, and its role for organizational decision making and performance boost.
• Potential to achieve results with personal efforts and team coordination
• Ability to work in a challenging environment and sustain pressure.
• Have a keen attention to accuracy, proficiency, and time management.
• Good analytical skills and decision-making.
• Effective communication and negotiation skills

Skills – Job Specific:

• Strong expertise in writing SQL is a must.
• Good understanding and experience of Data Management on Big Data Hadoop Platform.
• Basic understanding of Telecom and cellular business.
• Understanding of BI & DWH solution development methodology and in general System Development Life cycle.
• Hands-on experience in developing and managing large Analytical Datamarts.
• Ability to provide quick and accurate solutions to address critical business needs for information and insights of business stakeholders.
• Strong expertise in data analysis.
• Basic knowledge in Analytics tools and technologies (e.g., Data warehouse, Hadoop).
• Skilled in data governance, including metadata management, data quality, data standard, etc. Knowledge of Hadoop, Big Data Tools & Utilities like HDFS, MapReduce, Apache Spark, Hive, YARN is must Knowledge of Teradata, Shell Scripting and Python